TensorFlow Jobs in Saudi

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Job Description: AI / ML Engineer Job Title: AI / ML Engineer Experience: 3 11 Years Location: Riyadh (Onsite) Employment Type: Full-Time Job Overview We are seeking a skilled AI / ML Engineer with 3 11 years of experience to design, develop, deploy, and optimize machine learning and generative AI solutions. The ideal candidate will have hands-on expertise in building scalable AI/ML models, working with cloud-native AI platforms, and implementing production-ready machine learning pipelines. Experience with modern AI frameworks, large language models (LLMs), and MLOps practices is highly desirable. Key Responsibilities Design, develop, train, and deploy machine learning and deep learning models for enterprise applications. Build and optimize end-to-end ML pipelines for data ingestion, model training, evaluation, and deployment. Develop Generative AI and LLM-powered applications using modern AI frameworks. Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions. Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security. Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation. Implement MLOps best practices including model versioning, monitoring, and CI/CD automation. Stay current with advancements in AI, machine learning, and cloud AI services. Required Technical Skills Cloud AI Platforms Hands-on experience with GCP Vertex AI or Azure Machine Learning or AWS SageMaker . Experience with Azure OpenAI or AWS Bedrock for Generative AI solutions. Experience with BigQuery ML and Dataflow for data processing and machine learning workflows. Programming &amp; Machine Learning Strong proficiency in Python . Experience developing machine learning solutions using TensorFlow or PyTorch . Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts. Generative AI &amp; LLM Frameworks Experience with Hugging Face and LangChain for building LLM-powered applications. Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases is preferred. Data Engineering &amp; Analytics Experience with Databricks for data engineering, model development, and analytics workflows. Strong understanding of data preprocessing, feature engineering, and large-scale data processing. MLOps &amp; Deployment Experience deploying machine learning models into production. Knowledge of Docker, Kubernetes, CI/CD pipelines, and model monitoring is an advantage. Qualifications Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field. 3 11 years of professional experience in AI, Machine Learning, or Data Science. Strong analytical, mathematical, and problem-solving skills. Experience working in Agile development environments. Excellent communication and collaboration skills. Preferred Skills Experience with Large Language Models (LLMs) and Generative AI applications. Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents. Experience with distributed model training and cloud-native AI architectures. Cloud certifications in AWS, Azure, or Google Cloud are a plus. Key Technology Stack Cloud AI: GCP Vertex AI or Azure Machine Learning or AWS SageMaker Generative AI: Azure OpenAI or AWS Bedrock and Large Language Models (LLMs) Data Processing: BigQuery ML and Dataflow and Databricks Programming: Python Machine Learning Frameworks: TensorFlow or PyTorch LLM Frameworks: Hugging Face or LangChain MLOps: Docker and Kubernetes and CI/CD (Preferred) Share</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><h2>Qualifications</h2><p>Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.</p><p>3 11 years of professional experience in AI, Machine Learning, or Data Science.</p><p>Strong analytical, mathematical, and problem-solving skills.</p><p>Experience working in Agile development environments.</p><p>Excellent communication and collaboration skills.</p><h2>Preferred Skills</h2><p>Experience with Large Language Models (LLMs) and Generative AI applications.</p><p>Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents.</p><p>Experience with distributed model training and cloud-native AI architectures.</p><p>Cloud certifications in AWS, Azure, or Google Cloud are a plus.</p><p></p></section>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are seeking AI / ML Engineers across multiple experience levels (T1 T5) to design, develop, train, deploy, and optimize machine learning models and AI solutions throughout the complete machine learning lifecycle. Candidates will work on data preparation, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement using modern cloud AI platforms and open-source machine learning frameworks. The role offers opportunities ranging from entry-level implementation to enterprise AI architecture and technical leadership.</p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, train, evaluate, and deploy machine learning and AI solutions.</li><li>Build scalable ML pipelines from data preparation through production deployment.</li><li>Develop supervised, unsupervised, deep learning, and generative AI models.</li><li>Perform feature engineering, data preprocessing, model validation, and hyperparameter optimization.</li><li>Integrate ML models into enterprise applications and cloud-native environments.</li><li>Deploy AI models using managed cloud ML services and MLOps practices.</li><li>Monitor model performance, drift, accuracy, and production reliability.</li><li>Collaborate with Data Scientists, Data Engineers, Software Engineers, and DevOps teams.</li><li>Optimize model performance, scalability, and inference latency.</li><li>Document models, experiments, evaluation metrics, deployment processes, and governance standards.</li><li>Follow AI security, responsible AI, and model governance best practices.</li></ul><p><strong>Required Technical Skills</strong></p><ul><li><strong>Cloud AI Platforms</strong>: GCP Vertex AI or BigQuery ML or Dataflow, Azure ML or Azure OpenAI, AWS SageMaker or Amazon Bedrock</li><li><strong>Programming</strong>: Python</li><li><strong>Machine Learning Frameworks</strong>: TensorFlow or PyTorch</li><li><strong>Generative AI &amp; LLM Frameworks</strong>: HuggingFace or LangChain</li><li><strong>Data &amp; Analytics</strong>: Databricks</li><li><strong>Additional Skills</strong>: Machine Learning, Deep Learning, NLP, Computer Vision, Model Evaluation, Feature Engineering, API Development, Git</li></ul><p><strong>Responsibilities by Tier</strong></p><p><strong>T1 Associate AI / ML Engineer (0 - 2 Years)</strong></p><ul><li><strong>Role Focus:</strong> Learning, implementation, and execution under supervision.</li><li><strong>Responsibilities</strong><ul><li>Assist in data preparation, cleansing, and feature engineering.</li><li>Develop simple machine learning models using established frameworks.</li><li>Support model training, testing, and validation activities.</li><li>Deploy models under senior guidance.</li><li>Maintain documentation for datasets, experiments, and models.</li><li>Debug ML pipelines and resolve basic issues.</li><li>Learn cloud AI platforms and development best practices.</li><li>Follow coding standards, security policies, and project guidelines.</li></ul></li></ul><p><strong>T2 AI / ML Engineer (2 - 4 Years)</strong></p><ul><li><strong>Role Focus:</strong> Independent development and delivery.</li><li><strong>Responsibilities</strong><ul><li>Build and deploy production-ready machine learning models.</li><li>Perform feature engineering and model optimization.</li><li>Develop reusable ML components and inference APIs.</li><li>Implement model evaluation and performance monitoring.</li><li>Integrate ML models into enterprise applications.</li><li>Collaborate with cross-functional engineering teams.</li><li>Troubleshoot production AI issues.</li><li>Contribute to model documentation and deployment automation.</li></ul></li></ul><p><strong>T3 Senior AI / ML Engineer (5 - 7 Years)</strong></p><ul><li><strong>Role Focus:</strong> Technical ownership and solution development.</li><li><strong>Responsibilities</strong><ul><li>Design end-to-end AI and machine learning solutions.</li><li>Lead development of complex ML pipelines and AI applications.</li><li>Optimize training pipelines for performance and scalability.</li><li>Guide junior engineers and perform technical reviews.</li><li>Implement Responsible AI, explainability, and governance practices.</li><li>Improve model reliability, monitoring, and lifecycle management.</li><li>Collaborate with business stakeholders to translate requirements into AI solutions.</li><li>Support architecture decisions for enterprise AI initiatives.</li></ul></li></ul><p><strong>T4 Lead AI / ML Engineer (8 - 11 Years)</strong></p><ul><li><strong>Role Focus:</strong> Technical leadership and enterprise solution delivery.</li><li><strong>Responsibilities</strong><ul><li>Lead architecture and delivery of enterprise AI platforms and machine learning solutions.</li><li>Define technical standards, reusable frameworks, and engineering best practices.</li><li>Lead multiple AI initiatives across business domains.</li><li>Drive cloud-native AI solution design and deployment.</li><li>Review solution architecture, model performance, and production readiness.</li><li>Mentor engineering teams and provide technical leadership.</li><li>Collaborate with enterprise architects, product owners, and business leaders.</li><li>Improve AI platform scalability, governance, security, and operational excellence.</li></ul></li></ul><p><strong>T5 Principal AI / ML Architect (12+ Years)</strong></p><ul><li><strong>Role Focus:</strong> Enterprise AI strategy, architecture, and innovation.</li><li><strong>Responsibilities</strong><ul><li>Define enterprise AI/ML strategy and long-term technology roadmap.</li><li>Own architecture decisions for large-scale AI and machine learning platforms.</li><li>Lead enterprise-wide AI transformation initiatives.</li><li>Establish standards for Responsible AI, governance, security, and compliance.</li><li>Evaluate emerging AI technologies, frameworks, and cloud services.</li><li>Drive innovation in Generative AI, LLMs, and advanced machine learning solutions.</li><li>Provide executive-level technical guidance and strategic recommendations.</li><li>Lead technical communities, architecture reviews, and cross-functional AI governance.</li><li>Influence organizational AI adoption and engineering excellence across multiple programs.</li></ul></li></ul><p><strong>Preferred Certifications</strong></p><ul><li>One or more of the following certifications is highly preferred: Google Professional Machine Learning Engineer, AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate, TensorFlow Developer Certificate</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p><strong>Preferred Qualifications</strong></p><ul><li>Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field.</li><li>Strong understanding of statistics, machine learning algorithms, deep learning, and generative AI concepts.</li><li>Experience with cloud AI platforms and modern ML frameworks.</li><li>Knowledge of MLOps, CI/CD, model deployment, and production monitoring is an advantage.</li><li>Strong analytical, communication, and problem-solving skills.</li><li>Ability to work in Agile, cross-functional, and enterprise-scale environments.</li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Our subsidiary (Nabeh) is seeking for an experienced and highly skilled LLM Engineer to design, develop, and deploy Arabic-first Large Language Model (LLM) solutions to support AI-driven products and client projects, ensuring high-quality Arabic language understanding, generation, and contextual accuracy across enterprises.<br> Key Responsibilities1.<br> LLM Development &amp; NLP (Core) Design and fine-tune LLMs for Arabic language tasks Text generation, classification, summarization Arabic grammar correction, dialect handling Build and optimize RAG pipelines Develop prompt engineering strategies for Arabic + English contexts 2.<br> Data &amp; Arabic Language Engineering Build and curate Arabic datasets Handle: Dialects (Gulf, MSA, etc.<br>) Data cleaning, normalization Define evaluation benchmarks for Arabic LLM quality 3.<br> AI System Architecture Develop LLM-powered systems using: LangChain / LangGraph / Llama / OpenAI APIs Vector databases (ChromaDB, FAISS, etc.<br>) Integrate LLMs into: APIs Enterprise systems AI agents / copilots 4.<br> Production &amp; MLOps Deploy scalable AI systems using: Docker, Kubernetes Cloud platforms (Azure, AWS, GCP) Optimize: Latency Cost Throughput 5.<br> Cross-functional Collaboration Work with: PMs (scope, delivery, timelines) BAs (requirements translation → AI logic) QA (model validation &amp; test cases) Support client demos and AI solution design 6.<br> Governance Alignment (Critical for Nabeh) Ensure: AI outputs align with client expectations Traceability (data → model → output) Support: BRD validation (AI feasibility) UAT and acceptance criteria Required SkillsTechnical Strong in: Python (PyTorch / TensorFlow) NLP &amp; LLMs (Transformers, RAG) Experience with: LangChain / LLM frameworks Vector databases Prompt engineering Arabic AI (Mandatory) Native or fluent Arabic Experience in: Arabic NLP Dataset preparation for Arabic Handling dialects Engineering &amp; Deployment APIs (FastAPI / Flask) Microservices architecture Docker, Kubernetes CI/CD pipelines Language Requirements Arabic: Native / Fluent (MANDATORY) English: Professional (MANDATORY) Preferred Qualifications MSc or higher in AI / Data Science / NLP Experience in: Arabic LLMs (high priority) Government or enterprise AI projects Certifications: Azure AI / ML MLOps / Cloud certifications</span> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<p><strong>Job Overview</strong></p><p>We are seeking a motivated AI Engineer to join our dynamic team in Saudi Arabia.&nbsp;</p><p>This internship-focused role provides hands-on experience in designing, developing, and deploying AI-powered solutions that address real-world business challenges.</p><p>You will work closely with data scientists, software engineers, and product managers to deliver scalable, production-ready AI systems while gaining exposure to cutting-edge technologies and industry best practices.</p><p>&nbsp;</p><p><strong>About the Company</strong></p><p>We are a forward-thinking technology firm dedicated to leveraging artificial intelligence to transform industries.&nbsp;</p><p>Our culture emphasizes innovation, collaboration, and continuous learning.&nbsp;</p><p>We offer a supportive environment for interns to grow their technical capabilities and contribute to meaningful projects across various domains.</p><p>&nbsp;</p><p><strong>Key Responsibilities</strong></p><ul><li>Assist in researching, prototyping, and implementing AI/ML models aligned with business goals.</li><li>Prepare and process datasets, perform data cleaning, feature engineering, and exploratory data analysis.</li><li>Develop and optimize machine learning pipelines and APIs for deployment.</li><li>Collaborate with software engineers to integrate AI components into front-end and back-end systems.</li><li>Participate in model evaluation, testing, and benchmarking to ensure reliability and performance.</li><li>Document experiments, results, and technical specifications for reproducibility.</li><li>Contribute to the development of technical roadmaps and best practices for AI initiatives.</li><li>Stay updated with the latest AI/ML research and tools; share insights with the team.</li></ul><p>&nbsp;</p><p><strong>Qualifications and Requirements</strong></p><ul><li>Currently pursuing or recently completed a Bachelor's degree in Computer Science, Electrical Engineering, Data Science, AI/ML, or a related field (internship candidate status).</li><li>Fundamental understanding of machine learning concepts, algorithms, and evaluation metrics.</li><li>Proficiency in at least one programming language commonly used in AI (Python preferred).&lt; /li&gt;</li><li>Experience with data processing libraries (NumPy, pandas) and ML frameworks (scikit-learn, TensorFlow, PyTorch).</li><li>Familiarity with data visualization tools and techniques.</li><li>Basic knowledge of cloud services (e.g., AWS, Azure, or GCP) and containerization (Docker) is a plus.</li><li>Strong problem-solving skills, curiosity, and a collaborative mindset.</li><li>Excellent communication skills in English; Arabic language proficiency is a plus.</li></ul><p>&nbsp;</p><p><strong>Required Skills</strong></p><ul><li>Python programming</li><li>Machine learning fundamentals</li><li>Data preprocessing and feature engineering</li><li>Model development and evaluation</li><li>Version control (Git)</li><li>Ability to work in cross-functional teams</li></ul><p>&nbsp;</p><p><strong>Benefits and Perks</strong></p><ul><li>Structured internship program with paired mentors and regular feedback.</li><li>Hands-on project experience with potential for full-time opportunities.</li><li>Exposure to cloud platforms, ML tooling, and modern development practices.</li><li>Competitive stipend and relocation support where applicable.</li><li>Professional development resources, training sessions, and networking opportunities.</li></ul>

<b>Position Summary:</b><br>Our client is seeking a technical expert with deep understanding and practical experience in the Model as a Service (MaaS) field for the Saudi Riyadh project. You will be on-site as the bridge connecting customer business needs with LLM capabilities. Your key responsibility is to understand how customers use models, diagnose performance in specific scenarios, and collaborate with internal teams for targeted optimization to achieve the best balance of effect and cost, while utilizing language skills to optimize Arabic-related model tasks.<br><br><b>Responsibilities:</b><br><ul><li>Model Application Analysis and Diagnosis: Analyze LLM performance in inference, generation, and moderation, and replicate customer-reported bad cases.</li><li>Model Optimization and Tuning Support: Provide optimization suggestions like Prompt Engineering and Finetuning; collaborate with internal teams on model tuning, especially for Arabic processing.</li><li>Front-line Technical Support and Consulting: Provide professional technical support on MaaS platform usage, model selection, API calling, and cost optimization.</li><li>Performance and Cost Monitoring: Monitor key performance indicators (such as TPM, TTFT, success rate) and provide cost-effective model combination strategies.</li><li>Cross-Cultural Communication and Collaboration: Utilize language advantages to accurately understand customer needs in Arabic scenarios, ensuring lossless communication.</li></ul><br><b>Qualifications:</b><br><ul><li>LLM-related project experience (such as model evaluation, development, optimization, or technical support); experience in MaaS platforms or large AI companies is preferred.</li><li>Deep understanding of underlying LLM logic (Transformer, Tokenization, inference processes); experience in Prompt Engineering; familiar with model evaluation metrics and knowing deep learning on mainstream frameworks (TensorFlow, PyTorch).</li><li>Language: Mandarin: Native speaker level, used for highly efficient internal team collaboration. English: Fluent in spoken and written English, capable of participating in technical communication and reading/writing technical documents. Proficient in Arabic reading and writing, capable of processing and analyzing Arabic language.</li><li>On-site resident support at customer site; short-term business travel may be required.</li><li>Able to accept 7x24 on-call schedules, responding quickly to urgent customer needs.</li><li>Respect and understand local Saudi laws, regulations, business culture, and social customs.</li><li>Possess a high awareness of data security and privacy protection, strictly complying with company and customer data regulations.</li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>AI Expert: Generative AI, Azure &amp; 3D Modeling</b></p><p> </p><p><b>Job Summary</b></p><p>We are seeking a versatile and highly skilled AI Expert to join our innovative team. This role requires a unique blend of expertise in Large Language Models (LLMs) on the Azure platform and the application of AI in 3D modeling. The ideal candidate will be a creative technologist passionate about pushing the boundaries of generative AI, from developing intelligent Copilot agents to creating immersive 3D worlds. You will be responsible for designing, developing, and deploying cutting-edge AI solutions that span conversational AI and advanced 3D content generation.</p><p><b>Key Responsibilities</b></p><ul><li>Holistic AI Solution Design:&nbsp;Architect and implement end-to-end AI solutions that leverage the full spectrum of generative AI, including both language and visual modalities.</li><li>Conversational &amp; Agentic AI:</li><li>Design and develop sophisticated conversational AI agents using Microsoft Copilot Studio and the Azure AI ecosystem (including Azure OpenAI Service).</li><li>Build and implement LLM-based applications, leveraging frameworks like LangChain for complex Retrieval-Augmented Generation (RAG) and agentic workflows.</li><li>Integrate AI agents with enterprise data sources (e.g., SharePoint, SQL Server) and automate business processes using Power Automate.</li><li>AI for 3D Modeling:</li><li>Utilize and develop AI-powered tools to assist, automate, and enhance the creation of high-quality 3D models.</li><li>Design, implement, and train large-scale generative models (e.g., diffusion models) for generating 3D assets and environments from text or 2D images.</li><li>Create and manage scalable data pipelines for large, unstructured, multi-modal data sources (text, images, 3D models) to fuel machine learning initiatives.</li><li>MLOps &amp; Collaboration:</li><li>Take ownership of the full lifecycle of ML models, including deployment, containerization, CI/CD, and performance monitoring.</li><li>Collaborate closely with business stakeholders, designers, and research teams to translate product requirements into a cohesive technical roadmap.</li></ul><p><br></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p><b>Qualifications</b></p><ul><li>Experience:&nbsp;5+ years of hands-on experience in AI/ML engineering or data science, with a proven track record of building and deploying complex AI solutions.</li><li>Core Technical Skills:</li><li>Proficiency in Python and common ML/DL libraries (e.g., scikit-learn, TensorFlow, PyTorch).</li><li>Strong experience with the Azure AI/Data ecosystem, particularly Azure Machine Learning and Azure OpenAI Service.</li><li>Generative AI Expertise:</li><li>Hands-on experience with Microsoft Copilot Studio and building conversational agents.</li><li>Experience with generative models (GANs, Diffusion Models, LLMs) is a significant plus.</li><li>3D Modeling Skills:</li><li>A strong portfolio showcasing 3D modeling work is highly desirable.</li><li>Familiarity with 3D modeling software (e.g., Blender, Maya, ZBrush) and computational geometry is a plus.</li><li>Education:&nbsp;Bachelor's or Master's degree in Computer Science, Engineering, Graphic Design, or a related technical discipline.&nbsp;</li></ul><p><br></p></div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>We are seeking an experienced Data Scientist – Compliance (Banking) to develop, validate, and deploy advanced analytics and machine learning solutions that support regulatory compliance, financial crime prevention, and risk management initiatives within the banking environment.<br> The ideal candidate will combine strong technical expertise in data science with deep knowledge of banking regulations, AML/KYC processes, sanctions screening, and model risk management frameworks.<br> This role requires delivering robust, explainable, and audit-ready models that meet regulatory expectations and business objectives.<br> Key Responsibilities Design, develop, validate, and monitor machine learning and statistical models for compliance, financial crime detection, and risk management use cases.<br> Build predictive and anomaly detection models supporting AML, KYC, sanctions screening, transaction monitoring, customer risk scoring, and fraud detection programs.<br> Ensure all models comply with internal governance standards, regulatory requirements, and model risk management frameworks.<br> Perform model validation, performance testing, stability analysis, bias assessment, and explainability reviews.<br> Develop and maintain comprehensive model documentation, validation reports, and audit-ready artifacts.<br> Collaborate with Compliance, Risk, Financial Crime, Technology, and Data Engineering teams to translate business requirements into analytical solutions.<br> Analyze large-scale structured and unstructured datasets to identify patterns, trends, and emerging compliance risks.<br> Implement model monitoring frameworks, performance dashboards, and periodic model reviews.<br> Support internal audits, regulatory examinations, and independent model validation exercises.<br> Stay current with evolving regulatory requirements, industry best practices, and advancements in AI/ML technologies.<br> Mentor junior data scientists and contribute to the establishment of data science best practices and governance standards.<br> Required Qualifications Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Finance, or a related quantitative discipline.<br> 6–8+ years of experience in Data Science, Machine Learning, or Advanced Analytics within Banking or Financial Services .<br> Strong programming expertise in Python and SQL .<br> Hands-on experience with machine learning libraries and frameworks including scikit-learn , XGBoost , PyTorch , and/or TensorFlow .<br> Experience developing and validating classification, anomaly detection, forecasting, and risk-scoring models.<br> Strong understanding of Model Risk Management (MRM) frameworks, model governance, and validation methodologies.<br> Knowledge of banking regulatory requirements and compliance controls.<br> Experience working with cloud and big-data ecosystems is an advantage.<br> Domain Expertise Anti-Money Laundering (AML) Know Your Customer (KYC) Customer Due Diligence (CDD) / Enhanced Due Diligence (EDD) Sanctions Screening Transaction Monitoring Financial Crime Risk Management Regulatory Compliance and Reporting Preferred Skills Experience with explainable AI (XAI) techniques and model interpretability tools.<br> Knowledge of regulatory expectations related to AI/ML model governance in financial institutions.<br> Familiarity with MLOps, model deployment, monitoring, and lifecycle management.<br> Strong analytical thinking, problem-solving, and stakeholder management skills.<br> Excellent communication and documentation abilities with experience presenting to risk, compliance, audit, and senior leadership teams.<br> Success Metrics Delivery of compliant, accurate, and explainable machine learning models.<br> Successful completion of model validation and regulatory reviews.<br> Reduction in false positives and improved detection effectiveness in compliance programs.<br> High-quality audit-ready documentation and governance adherence.<br> Effective collaboration with Compliance, Risk, and Technology stakeholders.<br></span> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Senior Generative AI (GenAI) Engineer Description InnovationTeam is a forward-thinking technology company that specializes in delivering advanced AI-driven solutions to enterprises and government organizations.<br> We are currently seeking a highly skilled Senior Generative AI (GenAI) Engineer to join our AI team.<br> As a Senior GenAI Engineer at InnovationTeam , you will be responsible for designing, developing, and deploying large-scale generative AI solutions.<br> You will work closely with cross-functional teams to translate business and technical requirements into robust AI systems and bring them into production.<br> This role requires deep expertise in modern AI architectures, large language models, and production-ready software engineering practices.<br> The ideal candidate is highly motivated, detail-oriented, and capable of owning AI solutions end to end.<br> At InnovationTeam , we value innovation, collaboration, and continuous learning.<br> We provide a flexible and inclusive work environment where your expertise is recognized and opportunities for professional growth are continuously supported.<br> Role Overview We are seeking a skilled AI Engineer with a strong focus on Generative AI technologies to develop, optimize, and deploy AI Agents and solutions.<br> The role involves working on real-world use cases and data analytics problems and delivering production-ready AI systems.<br> Key Responsibilities · Design, develop, and optimize Generative AI solutions (LLMs, RAG systems, AI agents).<br> · Fine-tune, evaluate, and deploy large language models for enterprise use cases.<br> · Build and maintain end-to-end AI pipelines, from data ingestion to inference.<br> · Implement Retrieval-Augmented Generation (RAG) using vector databases and knowledge stores.<br> · Integrate GenAI solutions with existing systems via APIs and microservices.<br> · Optimize model performance, latency, and cost on cloud platforms (OCI, AWS, Azure, or GCP).<br> · Collaborate with product, data, and engineering teams to translate business needs into AI solutions.<br> · Ensure AI solutions follow best practices in security, governance, and responsible AI.<br> · Stay up to date with the latest developments in GenAI, LLMs, and AI tooling.<br> Required Skills &amp; Qualifications · Minimum 5 years of professional experience in AI / Machine Learning.<br> · Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.<br> · Proficiency in programming languages such as python , Java , and Ruby.<br> · Strong experience with Large Language Models (LLMs) (e.<br>g., GPT, LLaMA, Mistral, etc.<br>). · Hands-on experience with Python and AI/ML frameworks (PyTorch, TensorFlow).<br> · Solid understanding of NLP, deep learning, and transformer architectures.<br> · Experience with RAG architectures, vector databases (FAISS, OpenSearch, Pinecone, etc.<br>). · Strong software engineering skills (APIs, REST, microservices, Docker, Kubernetes).<br> · Experience deploying AI workloads on cloud platforms (OCI preferred).<br> · Excellent problem-solving and analytical skills.<br> · Excellent command of English (written and spoken).<br> Nice to Have · Experience with GPU-based training and inference.<br> · Familiarity with MLOps / LLMOps practices.<br> · Experience in regulated or enterprise environments.<br> · Knowledge of AI governance, ethics, and compliance frameworks.<br> What We Offer · Opportunity to work on cutting-edge Generative AI projects.<br> · Collaborative, innovation-driven environment.<br> · Competitive compensation package.<br> · Access to modern AI infrastructure and cloud resources.<br> · Professional growth and learning opportunities.<br></span> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <b>Job Details:</b><br><br>Job Description: <p><b>About the role</b></p><br><br><p><br>Join Intel's Agentic Platform team as we build a regional engineering presence in Saudi Arabia, in alignment with Saudi Vision 2030 and the Kingdom's ambition to become a global AI hub. You will help build the software, tooling, and integrations behind Intel's agentic AI platform - the systems that let enterprise customers across the Kingdom and the wider MENA region deploy, operate, and scale AI agents on Intel hardware.</p><br><br><p><br>This is a hands-on engineering role for an early-career software engineer. You will write production code, contribute to platform features end-to-end, and grow alongside global Intel teams that are shipping the agentic AI stack today.<br><b>What you'll do</b></p><br><br><p><br>• Build and maintain features of the Agentic Platform: Front End UI, APIs, services, tooling, and integrations that customer teams rely on<br>• Contribute to the platform's deployment, observability, and quality across Intel hardware (Xeon, Gaudi, Arc / iGPU)<br>• Collaborate with global Intel engineering teams on shared codebases - code reviews, design discussions, and on-call rotations<br>• Work directly with the Regional Customer Success Engineering team to translate field feedback into platform improvements<br>• Document features and write internal technical content in both English and Arabic, supporting bilingual engineering and partner communication<br>• Participate in regional customer engagements, partner sessions, and Vision 2030 ecosystem activities (e.g., LEAP, Global AI Summit) as a technical representative of the team</p><br><br><br><br><b>Qualifications:</b><p><b>What we're looking for (minimum requirements)</b></p><br><br><p><br>• Bachelor's degree in Computer Science, Software Engineering, or a related engineering field<br>• 1-3 years of software engineering experience (internships, co-ops, and meaningful open-source contributions are counted)<br>• Proficiency in at least one of: Python, TypeScript, Go, C++, Rust, React, JavaScript<br>• Comfortable with Linux, Git, and command-line development<br>• Familiarity with REST APIs, HTTP-based services, and basic SQL (SQLite or PostgreSQL)<br>• Comfortable reading unfamiliar codebases and learning new technologies quickly<br>• Working proficiency in both Arabic and English - able to participate in technical discussions, write documentation, and communicate with customers and partners in both languages<br><b>Nice to have</b></p><br><br><p><br>• Experience with Docker and containerized development<br>• Exposure to AI / ML frameworks (PyTorch, TensorFlow) or LLM tooling (LangChain, LlamaIndex, Anthropic SDKs)<br>• Open-source contributions, technical blog posts, or participation in regional AI / developer communities (e.g., SDAIA, Saudi AI Society, GCC tech meetups)<br>• Prior internship or graduate experience at a global technology company</p><br><br><br><p><i>* Job posting details (such as work model, location or time type) are subject to change.</i></p><br><br><br><br><br><br>Job Type:Experienced Hire<br><br>Shift:Shift 1 (Saudi Arabia)<br><br>Primary Location: Saudi Arabia, Riyadh<br><br>Additional Locations:<br><br><br><br>Business group:Intel makes possible the most amazing experiences of the future. You may know us for our processors. But we do so much more. Intel invents at the boundaries of technology to make amazing experiences possible for business and society, and for every person on Earth. Harnessing the capability of the cloud, the ubiquity of the Internet of Things, the latest advances in memory and programmable solutions, and the promise of always-on 5G connectivity, Intel is disrupting industries and solving global challenges. Leading on policy, diversity, inclusion, education and sustainability, we create value for our stockholders, customers, and society.<br><br>Posting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/A<br><p><b>Work Model for this Role</b></p><br><br>This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.<br><p>*</p><br><br><br><br> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><strong>Lead delivery projects with our clients on a wide range of topics:</strong></p> <ul> <li>Lead and deliver client engagements across a broad range of Data Science, AI, and Generative AI topics, including enterprise AI transformation, analytics, and intelligent automation initiatives.</li> <li>Develop Data &amp; AI strategies, operating models, and implementation roadmaps aligned with client business objectives and digital transformation agendas.</li> <li>Design and deliver advanced analytics, Machine Learning, Generative AI, and Agentic AI solutions across cloud ecosystems including Microsoft Azure, Azure OpenAI, AWS, and Google Cloud Platform (GCP).</li> <li>Design and implement LLM-powered solutions, including RAG architectures, AI agents, prompt engineering frameworks, orchestration layers, and vector database integrations.</li> <li>Lead functional data architecture, data modelling, and data engineering activities, including ETL/ELT pipelines, API integrations, and structured/unstructured data processing to maximize enterprise data value.</li> <li>Develop and deploy Machine Learning and AI models, including predictive analytics, supervised and unsupervised learning, forecasting, NLP, recommendation engines, and quantitative analysis use cases.</li> <li>Support the setup of scalable AI/ML deployment environments through MLOps practices, model lifecycle management, monitoring, and governance frameworks.</li> <li>Deliver data platform modernization, migration, and AI enablement initiatives leveraging modern cloud-native and enterprise data technologies.</li> <li>Implement enterprise data governance and Responsible AI frameworks, including data quality management, master data management, AI governance, security, compliance, and data sovereignty considerations.</li> <li>Support organizational adoption and business readiness for Data &amp; AI solutions through stakeholder engagement, training, and operating model enablement.</li> <li>Contribute to business development activities, proposal development, thought leadership, and the expansion of Sia s AI and Data offerings, accelerators, and platforms, including SiaGPT.</li> </ul> <p><strong>In addition, we are seeking technical experience across all or some of the below:</strong></p> <ul> <li>Strong foundation in Data Science, Machine Learning, and Generative AI, with practical experience delivering AI use cases in enterprise environments.</li> <li>Hands-on experience with Python-based AI/ML ecosystems (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch, LangChain).</li> <li>Experience designing and deploying LLM and Agentic AI solutions, including RAG architectures, AI agents, prompt engineering, orchestration frameworks, and vector databases.</li> <li>Knowledge of modern AI platforms and cloud ecosystems such as Microsoft Azure AI, Azure OpenAI, AWS, Google Cloud, Databricks, or Snowflake.</li> <li>Experience with data engineering and data architecture concepts, including ETL pipelines, APIs, structured/unstructured data processing, and enterprise data platforms.</li> <li>Familiarity with MLOps / AIOps practices, model lifecycle management, monitoring, governance, and scalable deployment approaches.</li> <li>Understanding of AI governance, responsible AI, security, and data sovereignty requirements, particularly relevant for public sector and regulated industries in KSA and the GCC.</li> <li>Experience with business intelligence and visualization tools such as Power BI, Tableau, or similar.</li> <li>Ability to translate business problems into AI-driven operating models, analytics solutions, and transformation initiatives.</li> <li>Exposure to sector-specific AI use cases across industries such as Government, Energy, Utilities, Retail, Transportation, Financial Services, or Healthcare.</li> <li>Strong understanding of enterprise digital transformation environments, including integration with CRM, ERP, workflow, and customer platforms.</li> <li>Experience contributing to or leading AI strategy, use case prioritization, PoCs, MVPs, and enterprise-scale AI implementation programs.</li> <li>Familiarity with Agile delivery methodologies and cross-functional product delivery teams.</li> <li>Fluency in English is required; Arabic language proficiency is strongly preferred. Previous experience working in Saudi Arabia or the GCC region is considered a strong advantage.</li> </ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p><b>To excel in this role, you should possess:</b></p> <ul> <li>Bachelor s degree in Computer Science, Data Science, Artificial Intelligence, Information Systems, Software Engineering, Mathematics, Statistics, or a related quantitative field.</li> <li>Master s degree in a relevant discipline.</li> <li>4 10 years of professional experience in Data Science, AI, Analytics, or Digital Transformation, preferably within a consulting environment.</li> <li>Proven experience delivering AI/Data projects from strategy and use case definition through implementation and deployment.</li> <li>Experience working with enterprise and government stakeholders in KSA or the GCC.</li> <li>Strong client-facing communication and presentation skills, with the ability to engage senior stakeholders and translate technical concepts into business value.</li> <li>Ability to manage workstreams independently and contribute to proposal development, business development activities, and client relationship management.</li> <li>Relevant certifications in cloud, AI, or analytics platforms are considered a plus (e.g., Microsoft Azure AI, AWS Machine Learning, Google Cloud AI, Databricks).</li> <li>Fluency in English and Arabic is required.</li> <li>Experience in local networks and aiding in business development, proposal, and RFPs</li> <li>It is essential to work independently, functionally, and cross-functionally with large client and vendor teams to deliver quality and comprehensive solutions.</li> <li>Strong relationship management skills, with the ability to build networks and influence stakeholders effectively</li> <li>Exceptional analytical, communication, and interpersonal skills</li> <li>An entrepreneurial mindset with a passion for innovation and problem-solving</li> </ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><span><strong>Job Purpose</strong></span></p><br><ul><li><span>The Lead Specialist, Data Science &amp;&nbsp;Analytics,&nbsp;acts as a technical leader and senior practitioner, driving development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across&nbsp;Maaden.&nbsp;</span></li><li><span>The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.&nbsp;</span></li><li><span>Lead Specialist, Data Science &amp; Analytics&nbsp;is to analyze data, extract insights, and build predictive models that help organizations make smarter decisions and solve difficult problems. By blending expertise in statistics, computer science, and business strategy, they not only analyze complex datasets but also build predictive models that improve operations and shape long-term decisions. With nearly every industry leaning on data today, the demand for skilled professionals continues to grow&nbsp;</span></li></ul><p><span><strong>Key Accountabilities:</strong></span></p><br><p><span><strong>1.&nbsp;Lead End-to-End Data Science Delivery&nbsp;</strong></span></p><br><ul><li><span>Developing,&nbsp;implementing&nbsp;and&nbsp;maintaining&nbsp;databases and data collection systems&nbsp;</span></li><li><span>Own the full lifecycle of ML/AI initiatives&nbsp;-&nbsp;from problem framing, data exploration, feature engineering, model development, validation, and&nbsp;MLOps&nbsp;handover.&nbsp;</span></li><li><span>Deliver scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.&nbsp;</span></li><li><span>Performing statistical analysis to understand and interpret data insights&nbsp;</span></li><li><span>Applying data mining techniques to&nbsp;identify&nbsp;patterns, trends, and relationships in large datasets&nbsp;</span></li><li><span>Building predictive models and machine learning algorithms to forecast future outcomes&nbsp;</span></li><li><span>Creating clear data visualizations and reports to communicate findings to stakeholders&nbsp;</span></li><li><span>Working with cross-functional teams to understand business needs and provide data-driven solutions&nbsp;</span></li><li><span>Design and&nbsp;maintain&nbsp;reliable data pipelines and models in partnership with data engineering to ensure data is&nbsp;accurate,&nbsp;timely, and trustworthy for downstream use</span></li><li><span>Ensuring data security and compliance with relevant regulations&nbsp;</span></li><li><span>Drive experimentation, model versioning, automated retraining, and continuous improvement.&nbsp;</span></li></ul><p><span><strong>2.&nbsp;Translate Business Needs into AI/Analytics Solutions</strong>&nbsp;</span></p><br><ul><li><span>Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions&nbsp;</span></li><li><span>Engage BU/domain stakeholders to&nbsp;identify&nbsp;value creation opportunities and convert them into actionable analytics use cases.&nbsp;</span></li><li><span>Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data &amp; AI leadership and business teams.&nbsp;</span></li></ul><p><span><strong>3.&nbsp;Industrialize AI/ML Models (ML&nbsp;Ops &amp; Architecture)</strong>&nbsp;</span></p><br><ul><li><span>Partner with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.&nbsp;</span></li><li><span>Set standards for production deployment, testing, monitoring, drift handling, and lifecycle governance.&nbsp;</span></li><li><span>Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins&nbsp;</span></li><li><span>Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements&nbsp;</span></li></ul><p><span><strong>4. Responsible AI, Quality &amp; Governance</strong>&nbsp;</span></p><br><ul><li><span>Ensure compliance with&nbsp;Maaden’s Responsible AI, data quality, and data governance frameworks.&nbsp;&nbsp;</span></li><li><span>Promote reproducibility, documentation, lineage tracking, and auditability across all data science assets.&nbsp;</span></li><li><span>Ensure transparency, explainability, and continuous model governance across production and enterprise environments&nbsp;</span></li></ul><p><span><strong>5.&nbsp;Stakeholder Management &amp; Value Realization</strong>&nbsp;</span></p><br><ul><li><span>Communicate insights, results, risks, and recommendations to decision-makers using compelling narratives and visualization.&nbsp;&nbsp;</span></li><li><span>Track value realization,&nbsp;adoption&nbsp;metrics, and operational impact to ensure measurable benefit.&nbsp;</span></li></ul><p><span><strong>Minimum Qualification, Experience and Core Competencies:</strong></span></p><br><p><span><strong>Minimum Qualifications:&nbsp; &nbsp;</strong></span></p><br><ul><li><span>Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or related fields.&nbsp;</span></li></ul><p><span><strong>Minimum Experience:</strong>&nbsp;</span><br>&nbsp;</p><br><ul><li><span><strong>Minimum Experience:</strong>&nbsp;&nbsp;</span></li><li><span>6+&nbsp;years’ experience in&nbsp;Data Science / Advanced Analytics with industrial, mining, or heavy-asset environments&nbsp;preferred.&nbsp;Including&nbsp;at least 2 years leading or mentoring analytics professionals&nbsp;</span></li><li><span>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.&nbsp;</span></li><li><span>Strong&nbsp;proficiency&nbsp;with modern ML frameworks and cloud platforms (TensorFlow,&nbsp;PyTorch, Azure, AWS)&nbsp;–&nbsp;Microsoft AI Factory&nbsp;</span></li><li><span>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering&nbsp;teams.&nbsp;</span></li><li><br><span><strong>Machine Learning &amp; Advanced Analytics</strong></span><ul><li><span>Hands-on experience developing and deploying <strong>machine learning models</strong>, including <strong>time-series forecasting, predictive modeling, and optimization use cases</strong></span></li><li><span>Strong understanding of <strong>model performance, validation, stability, and business impact</strong></span></li></ul></li><li><span><strong>Generative AI &amp; AI Agents</strong></span><ul><li><span>Practical experience with <strong>Generative AI solutions</strong>, including <strong>copilots, intelligent automation, and agent-based workflows</strong></span></li><li><span>Ability to embed GenAI capabilities into enterprise processes to improve decision-making and operational efficiency</span><br><span>Good to Have Capabilities</span></li></ul></li><li><span><strong>Data Engineering (IT + OT)</strong></span><ul><li><span>Experience designing and maintaining <strong>data pipelines</strong> across IT and OT environments</span></li><li><span>Exposure to <strong>sensor data, streaming / real-time data processing</strong>, and industrial data sources</span></li><li><span>Ability to collaborate with data engineering teams to ensure reliable, timely, and trusted data flows</span></li></ul></li><li><span><strong>MLOps / AgentOps</strong></span><ul><li><span>Experience in <strong>model deployment and lifecycle management</strong>, including:&nbsp;</span><ul><li><span>Transition from model development to <strong>production and scale</strong></span></li><li><span>Monitoring, retraining, versioning, and drift management</span></li></ul></li><li><span>Familiarity with automation and operationalization of ML/AI workloads</span><br><span>Preferred Experience &amp; Platforms</span></li></ul></li><li><span><strong>Cloud &amp; Analytics Platforms</strong></span><ul><li><span>Experience working with enterprise cloud platforms, preferably:&nbsp;</span><ul><li><span><strong>Microsoft Azure Data Platform</strong></span></li><li><span><strong>Databricks AI Platform</strong></span></li><li><span><strong>Microsoft AI Foundry / Microsoft AI Factory</strong></span></li></ul></li><li><span>Understanding of cloud-native architectures for scalable analytics and AI solutions</span></li></ul></li></ul><p><span><strong>Core Competencies:</strong></span></p><br><ul><li><span><strong>Model Accuracy &amp; Reliability:</strong>&nbsp;Performance, drift stability, and operational uptime.&nbsp;&nbsp;</span></li><li><span><strong>Adoption &amp; Business Impact:</strong>&nbsp;Value realized, user adoption, integration success.&nbsp;&nbsp;</span></li><li><span><strong>Delivery Velocity:</strong>&nbsp;Timeliness of development cycles and deployment readiness.&nbsp;&nbsp;</span></li><li><span><strong>Compliance &amp; Quality:</strong>&nbsp;Alignment with Responsible AI, governance, and documentation standards.&nbsp;</span></li></ul><br> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>About Mozn MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.<br> We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence.<br> Our culture is built on the relentless pursuit of excellence and meaningful impact.<br> If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.<br> About the role We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions.<br> The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.<br> What you'll do Designing, building, and scaling machine learning models and infrastructure Deploying deep learning and generative models into production for public and private sector projects Optimizing ML training and inference for performance, latency, and scalability Monitoring, retraining, and improving deployed ML models Driving consultation efforts, providing expert guidance to client stakeholders Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data Develop backend services and APIs to expose AI capabilities securely and reliably Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.<br> You will be given a lot of responsibility and trust.<br> We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.<br> The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.<br> We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.<br> Bachelor's or master's degree in computer science or related field 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI.<br> Strong track record of projects across public and private sectors Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama) Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science) Familiarity with MLOps practices and automation pipelines Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment Experience building data ingestion, transformation, and processing pipelines Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.<br>js, or equivalent technologies Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces Working knowledge of frontend technologies such as React, Next.<br>js, JavaScript, TypeScript, HTML, and CSS Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services Ability to independently build functional AI applications from prototype through production Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery</span> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>About Mozn MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.<br> We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence.<br> Our culture is built on the relentless pursuit of excellence and meaningful impact.<br> If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.<br> About the role We are looking for a Senior AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions.<br> The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.<br> What you'll do Designing, building, and scaling machine learning models and infrastructure Deploying deep learning and generative models into production for public and private sector projects Optimizing ML training and inference for performance, latency, and scalability Monitoring, retraining, and improving deployed ML models Driving consultation efforts, providing expert guidance to client stakeholders Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data Develop backend services and APIs to expose AI capabilities securely and reliably Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.<br> You will be given a lot of responsibility and trust.<br> We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.<br> The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.<br> We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.<br> Bachelor's or master's degree in computer science or related field 5+ years of experience across software engineering, ML engineering, data science, data engineering and generative AI.<br> Strong track record of projects across public and private sectors Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama) Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science) Familiarity with MLOps practices and automation pipelines Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment Experience building data ingestion, transformation, and processing pipelines Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.<br>js, or equivalent technologies Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces Working knowledge of frontend technologies such as React, Next.<br>js, JavaScript, TypeScript, HTML, and CSS Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services Ability to independently build functional AI applications from prototype through production Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery</span> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>About Mozn MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.<br> We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence.<br> Our culture is built on the relentless pursuit of excellence and meaningful impact.<br> If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.<br> About the role We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions.<br> The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.<br> What you'll do Designing, building, and scaling machine learning models and infrastructure Deploying deep learning and generative models into production for public and private sector projects Optimizing ML training and inference for performance, latency, and scalability Monitoring, retraining, and improving deployed ML models Driving consultation efforts, providing expert guidance to client stakeholders Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data Develop backend services and APIs to expose AI capabilities securely and reliably Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.<br> You will be given a lot of responsibility and trust.<br> We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.<br> The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.<br> We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.<br> Bachelor's or master's degree in computer science or related field 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI.<br> Strong track record of projects across public and private sectors Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama) Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science) Familiarity with MLOps practices and automation pipelines Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment Experience building data ingestion, transformation, and processing pipelines Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.<br>js, or equivalent technologies Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces Working knowledge of frontend technologies such as React, Next.<br>js, JavaScript, TypeScript, HTML, and CSS Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services Ability to independently build functional AI applications from prototype through production Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery</span> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Years_of_experience"> <b>Years of experience</b> </div> <div class="col is-9 p5" data-automation-id="data_Years_of_experience"> No experience required </div> </div> <div class="row is-m v-align-top t-small "> <div class="col is-3 p5" data-automation-id="label_Degree"> <b>Degree</b> </div> <div class="col is-9 p5" data-automation-id="data_Degree"> Bachelor's degree / higher diploma </div> </div>

<h2 ><span lang="ar" dir="rtl">اعلان شركة معادن عن وظيفة&nbsp;أخصائي رئيسي علوم البيانات والتحليلات</span></h2><h3 ><span lang="ar" dir="rtl">وصف الوظيفة</span></h3><p ><span lang="ar" dir="rtl">يعمل أخصائي رئيسي علوم البيانات والتحليلات كقائد تقني وممارس أول، حيث يقود تطوير ونشر وتوسيع حلول التعلم الآلي (Machine Learning) والذكاء الاصطناعي (AI) والتحليلات المتقدمة عبر شركة معادن.</span></p><p ><span lang="ar" dir="rtl">يضمن الدور تصميم منتجات التحليلات والتحقق منها وتشغيلها على نطاق واسع وإدارتها واعتمادها، بما يحقق قيمة قابلة للقياس عبر التعدين والمعالجة والعمليات ووظائف المؤسسة.</span></p><p ><span lang="ar" dir="rtl">يقوم بتحليل البيانات واستخراج الرؤى وبناء النماذج التنبؤية لمساعدة المؤسسات على اتخاذ قرارات أفضل وحل المشكلات المعقدة. من خلال دمج الإحصاء وعلوم الحاسب واستراتيجية الأعمال، يعمل على تحليل البيانات وبناء نماذج تدعم تحسين العمليات وصناعة القرار طويل المدى.</span></p><h3 ><span lang="ar" dir="rtl">المهام والمسؤوليات الرئيسية</span></h3><h4 ><span lang="ar" dir="rtl">قيادة دورة حياة حلول علوم البيانات</span></h4><ul><li><p ><span lang="ar" dir="rtl">تطوير وتنفيذ وصيانة قواعد البيانات وأنظمة جمع البيانات.</span></p></li><li><p ><span lang="ar" dir="rtl">إدارة دورة حياة مشاريع الذكاء الاصطناعي والتعلم الآلي من تحديد المشكلة حتى التشغيل.</span></p></li><li><p ><span lang="ar" dir="rtl">تسليم نماذج قابلة للتوسع والتشغيل مع الالتزام بحوكمة البيانات ومعايير الذكاء الاصطناعي.</span></p></li><li><p ><span lang="ar" dir="rtl">إجراء التحليل الإحصائي لاستخراج الرؤى من البيانات.</span></p></li><li><p ><span lang="ar" dir="rtl">تطبيق تقنيات التنقيب عن البيانات لاكتشاف الأنماط والاتجاهات.</span></p></li><li><p ><span lang="ar" dir="rtl">بناء نماذج تنبؤية وخوارزميات تعلم آلي للتنبؤ بالنتائج المستقبلية.</span></p></li><li><p ><span lang="ar" dir="rtl">إنشاء تصورات وتقارير بيانات واضحة لعرض النتائج.</span></p></li><li><p ><span lang="ar" dir="rtl">العمل مع الفرق متعددة التخصصات لفهم احتياجات العمل وتقديم حلول قائمة على البيانات.</span></p></li><li><p ><span lang="ar" dir="rtl">بناء وإدارة خطوط بيانات موثوقة بالتعاون مع فرق هندسة البيانات.</span></p></li><li><p ><span lang="ar" dir="rtl">ضمان أمن البيانات والامتثال للأنظمة واللوائح.</span></p></li><li><p ><span lang="ar" dir="rtl">قيادة التجارب وتحسين النماذج وإعادة تدريبها بشكل مستمر.</span></p></li></ul><h4 ><span lang="ar" dir="rtl">تحويل احتياجات الأعمال إلى حلول ذكاء اصطناعي</span></h4><ul><li><p ><span lang="ar" dir="rtl">تطوير أطر عمل تجعل علوم البيانات قابلة للتطبيق على نطاق واسع داخل المؤسسة.</span></p></li><li><p ><span lang="ar" dir="rtl">التعاون مع أصحاب المصلحة لتحديد فرص القيمة وتحويلها إلى حالات استخدام.</span></p></li><li><p ><span lang="ar" dir="rtl">تحديد الفرضيات ومؤشرات الأداء ومعايير النجاح وخطط الحلول.</span></p></li></ul><h4 ><span lang="ar" dir="rtl">تشغيل نماذج الذكاء الاصطناعي (MLOps)</span></h4><ul><li><p ><span lang="ar" dir="rtl">دمج النماذج في الأنظمة التشغيلية والمنصات المؤسسية.</span></p></li><li><p ><span lang="ar" dir="rtl">تحديد معايير النشر والاختبار والمراقبة وإدارة دورة حياة النماذج.</span></p></li><li><p ><span lang="ar" dir="rtl">ضمان تكامل النماذج مع المنصات الرقمية والأنظمة التشغيلية.</span></p></li><li><p ><span lang="ar" dir="rtl">استخدام تقنيات التعلم الآلي والتحسين والرؤية الحاسوبية لتحسين الأداء.</span></p></li></ul><h4 ><span lang="ar" dir="rtl">حوكمة الذكاء الاصطناعي والجودة</span></h4><ul><li><p ><span lang="ar" dir="rtl">ضمان الالتزام بأطر الذكاء الاصطناعي المسؤول وحوكمة البيانات.</span></p></li><li><p ><span lang="ar" dir="rtl">تعزيز التوثيق وقابلية التتبع والشفافية عبر جميع النماذج.</span></p></li><li><p ><span lang="ar" dir="rtl">ضمان قابلية التفسير والمراجعة للنماذج التشغيلية.</span></p></li></ul><h4 ><span lang="ar" dir="rtl">التواصل وتحقيق القيمة</span></h4><ul><li><p ><span lang="ar" dir="rtl">عرض النتائج والرؤى باستخدام أسلوب سردي واضح ومؤثر.</span></p></li><li><p ><span lang="ar" dir="rtl">قياس القيمة المحققة ومؤشرات التبني والأثر التشغيلي.</span></p></li></ul><h3 ><span lang="ar" dir="rtl">المؤهلات</span></h3><ul><li><p ><span lang="ar" dir="rtl">بكالوريوس في علوم الحاسب، علوم البيانات، الهندسة، الرياضيات أو تخصص ذي صلة.</span></p></li></ul><h3 ><span lang="ar" dir="rtl">الخبرة المطلوبة</span></h3><ul><li><p ><span lang="ar" dir="rtl">خبرة من 8 إلى 10 سنوات في علوم البيانات أو التحليلات المتقدمة.</span></p></li><li><p ><span lang="ar" dir="rtl">يفضل خبرة في القطاعات الصناعية أو التعدين أو الأصول الثقيلة.</span></p></li><li><p ><span lang="ar" dir="rtl">خبرة لا تقل عن سنتين في قيادة أو توجيه فرق تحليل البيانات.</span></p></li></ul><h3 ><span lang="ar" dir="rtl">المهارات التقنية</span></h3><ul><li><p ><span lang="ar" dir="rtl">خبرة في TensorFlow وPyTorch ومنصات Azure وAWS.</span></p></li><li><p ><span lang="ar" dir="rtl">إتقان SQL ونمذجة البيانات والعمل مع فرق الهندسة.</span></p></li><li><p ><span lang="ar" dir="rtl">خبرة في النماذج التنبؤية وسلاسل الزمن والتحسين.</span></p></li><li><p ><span lang="ar" dir="rtl">خبرة في حلول الذكاء التوليدي وتطبيقات الوكلاء الذكيين (AI Agents).</span></p></li></ul><h3 ><span lang="ar" dir="rtl">البنية التحتية والتقنيات المفضلة</span></h3><ul><li><p ><span lang="ar" dir="rtl">تصميم خطوط بيانات عبر بيئات IT وOT.</span></p></li><li><p ><span lang="ar" dir="rtl">التعامل مع البيانات اللحظية وبيانات الحساسات.</span></p></li><li><p ><span lang="ar" dir="rtl">خبرة في MLOps وإدارة دورة حياة النماذج.</span></p></li><li><p ><span lang="ar" dir="rtl">خبرة في Azure Data Platform وDatabricks وMicrosoft AI Factory.</span></p></li></ul><h3 ><span lang="ar" dir="rtl">مؤشرات الأداء</span></h3><ul><li><p ><span lang="ar" dir="rtl">دقة وموثوقية النماذج واستقرارها.</span></p></li><li><p ><span lang="ar" dir="rtl">القيمة التجارية والأثر التشغيلي.</span></p></li><li><p ><span lang="ar" dir="rtl">سرعة التطوير والنشر.</span></p></li><li><p ><span lang="ar" dir="rtl">الالتزام بالحوكمة وجودة البيانات.</span></p></li></ul>