Quantum Solutions Engineer - Optimization or ML

Our client is a global deep-tech company developing neutral-atom quantum processors and software solutions for industrial and scientific applications.As part of its expansion in Saudi Arabia, the company is building a local Quantum Applications team and hiring across two specializations:Quantum OptimizationMachine Learning / Quantum Machine LearningThese are applied, client-facing positions rather than purely academic research roles. You will use quantum, classical and hybrid methods to solve real industrial problems and turn advanced research into practical customer solutions.What You Will DoTranslate complex industrial challenges into mathematical optimization or machine-learning problems.Deliver customer projects from technical discovery and feasibility assessment through solution development and handover.Build and test quantum, classical and hybrid approaches using Python, emulators, HPC resources and quantum processors.Establish strong classical baselines and evaluate whether a quantum approach offers a realistic advantage.Collaborate with customers, domain experts, scientists, software engineers and hardware teams.Produce maintainable code, technical documentation and clear customer-facing results.Take ownership of project milestones, technical risks and deliverables.We Are Looking ForYou should bring a strong background in one of the following areas:1- Optimization TrackCombinatorial optimization, operations research or applied mathematicsMathematical modelling and algorithm developmentScheduling, routing, logistics, graph or resource-allocation problemsMSc or PhD in a relevant technical field and at least three years of relevant experienceExperience with QUBO, Ising formulations or quantum optimization would be advantageous.2- Machine Learning TrackApproximately five or more years of experience in machine learning or applied scienceStrong experience building end-to-end ML pipelinesGraph machine learning, graph neural networks or related methodsResearch-to-production implementation and model benchmarkingQuantum or physics experience is valuable but not mandatory for exceptional machine-learning candidates. Training on the quantum layer can be provided to candidates with strong ML, mathematical and engineering foundations.Across Both TracksStrong Python and software-engineering practicesExperience evaluating and benchmarking algorithmsAbility to connect theoretical concepts with practical applicationsConfidence working directly with customers and international technical teamsProfessional fluency in EnglishWillingness to be based in Riyadh and work from the office two to three days per weekExperience in energy, logistics, industrial optimization, HPC or advanced computing would be an advantage. Arabic is helpful but not required.An initial training period with technical teams in France may be offered depending on the candidate’s background.