Applied AI Scientist, Simulation & Reinforcement Learning (AI)

Location: Remote, based in the United Kingdom; candidates must reside in the UK and have the legal right to work there. Visa sponsorship is not available.

Base salary: GBP 70,000–120,000 per year, plus bonus and equity.

Company

hirify.global builds AI-powered systems and intelligent robots for global supply chains, combining real-time decision-making and autonomous robotics for warehouse operations.

What you will do

• Own and develop the SimPy-based discrete-event simulator, including its logic, design decisions, technical debt, testing, reproducibility, and developer tooling.
• Build experiment infrastructure for orchestration, study management, reporting, automated benchmark runs, and customer-warehouse site data.
• Measure and reduce the sim-to-real gap using live operational data, parameter optimization, sensitivity analysis, and anomaly diagnosis.
• Model warehouse processes such as congestion, picker behavior, and queueing at appropriate levels of fidelity.
• Turn the simulator into a scalable Gymnasium/Gym-style reinforcement-learning environment; design, train, and evaluate policies against heuristic algorithms.
• Prototype and productionize learning-based components with ML, MLOps, and orchestration-engineering teams, while contributing to technical papers, patents, and publications where appropriate.

Requirements

• PhD in Computer Science, AI/ML, Robotics, Mathematics, Physics, Operations Research, or a related quantitative field; alternatively, an MSc with 5+ years of industry experience applying AI/ML or simulation to real-world problems.
• Hands-on experience building, extending, or validating simulators, ideally discrete-event simulation using SimPy or a similar framework.
• Practical experience with reinforcement learning, simulation-based agents, simulation for RL, and Gym-style environments.
• Strong Python and software-engineering fundamentals, including testing, code review, maintainable code, and reproducibility.
• Rigorous experimental and statistical thinking, including benchmarking, tuning, ablations, and uncertainty analysis.
• Experience in robotics, logistics, warehousing, or another operations-heavy domain.
• Publications in major AI, ML, robotics, or vision venues such as NeurIPS, ICML, ICLR, AAAI, RSS, CoRL, ICRA, IROS, CVPR, ICCV, or ECCV.
• Excellent written and verbal English communication skills, including the ability to explain uncertain results to technical and non-technical audiences.

Nice to have

• Experience with Optuna or comparable parameter-optimization tooling.
• Experience with multi-agent systems and simulation research.

Culture & Benefits

• Remote work from the United Kingdom within a small, collaborative Applied Data Science team.
• Work spanning research and production, with technology validated for deployment to customer robot fleets worldwide.
• Opportunities for continuous learning and career development.
• Compensation includes base salary, bonus, and equity.
• Equal opportunity employment practices apply.