Senior Quantum Solutions Engineer (W/M)

• Lead quantum optimization-related client projects from early technical discussions and problem framing to project delivery and handover.

• Support the Commercial team on the execution of feasibility studies and on the definition the state of work for future client projects

• Translate real-world problems into optimization formulations and evaluate solution strategies using a mix of analytical reasoning and numerical experimentation.

• Investigate and synthesize the state of the art (academic and industrial literature) to identify relevant directions, assess feasibility, and propose impactful research paths.

• Develop and scale quantum optimization solutions for clients’ use cases on Pasqal quantum processors. Also, improve and extend existing use cases;

• Design and run benchmarking and feasibility studies, including assessing the limitations of classical approaches and identifying realistic pathways toward quantum utility.

• Develop solutions and experiment pipelines in close collaboration with the software engineering team, using emulation backends locally and on HPC when relevant.

• Work hardware-aware: investigate realistic implementations on neutral-atom hardware (mainly using analog paradigms)

• Define blueprints of quantum utility for clients’ use-cases and collaborate closely with R&D hardware teams to bring them to fruition.

• Collaborate with internal and external stakeholders (Engineering, R&D, academic and industrial partners, and clients) throughout all phases of projects, ensuring alignment on technical scope, success criteria, and deliverables.

• Support team-wide execution and knowledge sharing, including helping on code/components outside your direct ownership when needed and contributing to ongoing scientific watch activities.

With a MSc or PhD in Combinatorial Optimization, Quantum Computing or in a related field with at least 5 years of experience in a similar role, you have most of the following assets:

• Strong background in combinatorial optimization: familiar with classical problems, linear programming, constrained programming, heuristics, metaheuristics, complexity theory, graph theory

• Strong background in quantum computing: in-depth understanding of quantum algorithms, Hamiltonian-based optimization, Ising formulations, adiabatic and variational approaches, noise mechanisms, state preparation errors, measurement statistics, and hardware constraints of neutral-atom QPUs;

• Methodological: ability to connect theoretical concepts with practical applications on current and future quantum hardware

• Delivery mindset: ability to explore, prototype, benchmark, and iterate on new approaches. Write clear technical reports

• Programming skills (Python): good software engineering practices such as version control, testing, and documentation

• Solid experience on algorithm evaluation & benchmarking: experiment design, reproducibility, performance analysis

• Able to collaborate with Engineering and R&D teams across different disciplines

• Project leadership: plan and drive projects end-to-end, manage milestones and risks

• Client-facing skills: relationship skills for interacting with clients and partners