Quantum Solutions Engineer - Scientific Machine Learning M/W - PASQAL

PASQAL designs and develops Quantum Processing Units and dedicated software tools. These innovative processors address applications which are out of the reach of the most powerful existing supercomputers, encompassing real-world challenges as well as fundamental science. As they are very low energy intensive, they will significantly contribute to reduce the carbon footprint of the computing industry.

PASQAL has partnerships with key users in the fields of energy, IT, finance, drug and chemical design, automotive. The maturity and potential of our technology and the quality of our scientific team has been rewarded several times at French, European and global levels.

Description

We are looking for a Quantum Solutions Engineer to join our Quantum Applications department and build client-facing solutions based on PASQAL’s quantum algorithm portfolio.

This application-driven engineering role focuses on adapting, integrating, and validating quantum and quantum-enhanced machine learning methods for real-world partner and client use-cases, with a strong focus on molecular and chemical applications.

The goal is to turn PASQAL’s existing methods into reliable client deliverables by combining scientific machine learning, Graph Machine Learning, and a nalog quantum computing .

Contributions to internal method improvement are welcome when they directly support project outcomes.

You will join as a Scientific Machine Learning Engineer specializing in chemistry applications, working at the interface between graph machine learning, quantum algorithms, and industrial use cases.

With strong engineering skills and an interest in quantum computing (physics background is a plus), you will:

• Adapt and implement PASQAL’s existing quantum and quantum-enhanced Graph ML algorithms for client datasets, scientific constraints, and performance targets.
• Translate scientific and chemical use cases into well-defined machine learning tasks, such as molecular property prediction, classification, ranking, or candidate screening.
• Select and implement suitable representations for molecules and chemical systems, including physicochemical descriptors, fingerprints, molecular graphs, and quantum feature representations.
• Integrate ML pipelines with quantum execution workflows, emulation and simulation platforms, PASQAL QPUs, and internal tooling.
• Collaborate closely with internal R&D teams to transfer quantum methods from research to application, clarify their assumptions and limitations, and select the most appropriate approach from PASQAL’s portfolio.
• Work closely with chemistry experts from clients and partners to understand the scientific meaning, quality, and limitations of molecular and experimental data.
• Produce maintainable code, technical documentation, benchmark reports, and handover material so delivered solutions can be reproduced, reused, and supported.