Quantum Solutions Engineer - Scientific Machine Learning M/W

Quantum Solutions Engineer - Scientific Machine Learning M/W Participate in the rapid development of a deep-tech scale-up at the forefront of the second quantum revolution! Will you join us? 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. · Maintain an active scientific and technological watch in Quantum Machine Learning, Graph Machine Learning, and molecular machine learning. This list is non exhaustive. About you Master’s degree or PhD in Machine Learning , Computational Chemistry or Quantum Physics 2+ years of experience in a similar role Strong ML engineering background, including model training and evaluation, classical baselines, metrics, and reproducible experimentation. Hands-on experience with graph-structured data and Graph Machine Learning, such as graph kernels, Graph Neural Networks, or graph representations. Familiarity with quantum computing or quantum mechanics concepts and constraints, including the differences between classical simulation, emulation, and hardware execution. Working knowledge of fundamental chemistry concepts and familiarity with molecular representations such as descriptors, fingerprints, molecular graphs, or SMILES. Strong interest in applying quantum computing to practical machine learning and scientific problems. Experience working with molecular, chemical, materials, or other scientific data. Ability to build end-to-end ML pipelines (pre/post-processing, integration with existing tools/platforms). Physics background (quantum/atomic/optics) is a plus. Delivery mindset and ownership (client-facing deliverables, pragmatism, trade-offs). Strong communication and collaboration with internal R&D, hardware, and platform teams. Right to work in USA without sponsorship is preferred. What we offer Flexible schedules to support work/life balance A dynamic, close-knit, collaborative, and diverse international team for co-workers An impactful role in a growing scale-up that is leading in the Neutral Atom Quantum Computing space Competitive benefit packages Lots of time off to enjoy the things you love outside of work Free time to learn and attend conferences/meetups Employment Terms : Full time, Direct hire, Hybrid Recruitment process An interview with our talent acquisition team via Teams Video meeting A 1 hour video interview with hiring manager via Teams Video meeting For technical roles: A technical Interview round via Teams Video with the hiring manager Final Interview An offer ! PASQAL is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace, as inclusion and diversity are essential to achieving our mission. We encourage applications from all qualified candidates, regardless of gender, music preference, ethnicity, age, religion or sexual orientation. Department Software Role Quantum Application Locations Chicago Remote status Hybrid Employment type Full-time Seniority Senior About Pasqal Joining Pasqal will give you the opportunity to take an active part in the rapid development of a DeepTech scale-up at the forefront of the second quantum revolution. You will be directly involved in one of the biggest challenges shaping the technological landscape of the 21st century. You will be working as part of a team of top-level scientists and engineers, in direct competition with the world's biggest players. Founded in 2019 Co-workers about 300