Reinforcement Learning Engineer/Scientist

£12000 - £80000 per annum


Tom Charles

Reinforcement Learning Engineer/Scientist


Approx Salary: £80,000 - £120,000.

Sponsorship is not available.

The company seeks exceptional candidates to pursue research in reinforcement learning and Bayesian optimization for autonomous decision-making under uncertainty. The successful applicant is expected to develop novel contributions allowing the field to advance in getting closer to real-world applications. Key research questions include but are not limited to scalable high-dimensional Bayesian optimization, Gaussian processes, Bayesian neural networks, safe and robust reinforcement learning, multi-agent reinforcement learning, and model-based reinforcement learning. This is an exceptional opportunity for research while collaborating with a diverse team with backgrounds ranging from mathematics and optimization to probability and game theory. These positions involve theoretical advances and aim to apply innovations in the real world, e.g., in self-driving scenarios, 5g networks, and many other chip design challenges.


  • Develop high-impact research output in reinforcement learning, Bayesian optimization, game theory, multi-agent learning, probabilistic modeling, and risk-averse learning.
  • Write research-level code capable of testing novel ideas and new approaches.
  • Aid in progressing research fields by open-sourcing code.


  • Ph.D. in Computer Science or related field.
  • Hands-on Experience in implementing reinforcement learning, Bayesian optimization, probabilistic modeling, and multi-agent algorithms.
  • Knowledge of Python, specifically PyTorch or TensorFlow, in addition to OpenAI Gym, GPFlow, and Pyro, among others

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.


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