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 Optimization
- Machine Learning / Quantum Machine Learning
These 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 Do
- Translate 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 For
You should bring a strong background in one of the following areas:
1- Optimization Track
- Combinatorial optimization, operations research or applied mathematics
- Mathematical modelling and algorithm development
- Scheduling, routing, logistics, graph or resource-allocation problems
- MSc or PhD in a relevant technical field and at least three years of relevant experience
Experience with QUBO, Ising formulations or quantum optimization would be advantageous.
2- Machine Learning Track
- Approximately five or more years of experience in machine learning or applied science
- Strong experience building end-to-end ML pipelines
- Graph machine learning, graph neural networks or related methods
- Research-to-production implementation and model benchmarking
Quantum 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 Tracks
- Strong Python and software-engineering practices
- Experience evaluating and benchmarking algorithms
- Ability to connect theoretical concepts with practical applications
- Confidence working directly with customers and international technical teams
- Professional fluency in English
- Willingness to be based in Riyadh and work from the office two to three days per week
Experience 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.
