We are looking for a candidate to join our Quantum Applications department delivery team to build and deliver client-facing solutions based on Pasqal’s quantum ML algorithm portfolio.

his is an application-driven engineering role focused on adapting, integrating, and deploying existing approaches to real-world partner and client use cases. The goal is to turn existing methods into reliable client deliverables; contributions to internal method improvement are welcome when they directly support project outcomes.

As a Senior machine learning engineer with around 5 years of professional experience at least with interest in quantum computing (physics background is a plus, not a requirement), you will:

Adapt and implement Pasqal’s existing quantum(-enhanced) graph ML algorithms to fit client datasets, constraints, and performance targets.

Build and maintain robust ML pipelines (data ingestion, preprocessing, training, evaluation, post-processing), including integration with quantum execution workflows, emulation/simulation platforms, and internal tooling.

Establish baselines, metrics, and acceptance criteria with stakeholders, and drive solution iterations until delivery requirements are met.

Collaborate closely with internal R&D teams to transfer methods from research to application, clarify assumptions/limits, and select the best approach from the portfolio for each use case.

Work with hardware and platform engineers to run solutions on Pasqal QPUs, taking into account hardware constraints, execution constraints, and reliability.

Work closely with domain experts from high profile enterprises and partners to deliver solutions on real-world business problems

Produce maintainable code, documentation, and handover material so delivered solutions can be reused and supported.

Keeping a regular scientific and technological watch.