Machine Learning Engineer (RL)

We are seeking a talented and experienced Machine Learning Engineer with a background in Reinforcement Learning to join our team. This engineer will contribute to the further development of Arena, a web-based software platform for reinforcement learning training and RLOps, and our open-source reinforcement learning library.

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• Collaborate with the team to understand requirements and design new features of the Arena platform and open-source framework.
  
• Develop scalable and reliable infrastructure to support reinforcement learning model training, LLM finetuning, model deployment, and management.
  
• Integrate existing machine learning frameworks and libraries into the platform and open-source framework, providing a range of algorithms, environments, and tools for reinforcement learning model development.
  
• Stay up-to-date with the latest advancements in AI, MLOps, reinforcement learning algorithms, tools, and techniques, and incorporate them into the platform as appropriate.
  
• Provide technical guidance and support to internal users and external customers using the Arena platform and open-source framework.
  

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• Master’s or Ph.D. degree in Computer Science, Engineering, or a related field, or 3+ years of relevant industry experience.
  
• Solid understanding of reinforcement learning algorithms and concepts, with hands‑on experience in building and training reinforcement learning models.
  
• Strong programming skills, with experience using reinforcement learning and ML frameworks and libraries (e.g. PyTorch, TensorFlow, Ray, Gym, RLLib, SB3, TRL), and MLOps tools.
  
• Solid understanding of hyperparameter optimisation techniques and strategies.
  
• Experience in building machine learning platforms or tooling for industrial or enterprise settings.
  
• Proficiency in data management techniques, including storage, retrieval, and pre‑processing of large‑scale datasets.
  
• Familiarity with model deployment and management, including the development of APIs, deployment pipelines, and performance optimisation.
  
• Experience in designing and developing cloud‑based infrastructure for distributed computing and scalable data processing.
  
• Deep understanding of software engineering and machine learning principles and best practices.
  
• Strong problem‑solving and communication skills, and the ability to work independently as well as in a team environment.
  

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• Competitive salary + significant stock options.
  
• 30 days of holiday, plus bank holidays, per year.
  
• Flexible working from home and 6-month remote working policies.
  
• Enhanced parental leave.
  
• Learning budget of £500 per calendar year for books, training courses and conferences.
  
• Company pension scheme.
  
• Regular team socials and quarterly all‑company parties.
  
• Bike2Work scheme.
  

Join the fast‑growing AgileRL team and play a key role in the development of cutting‑edge reinforcement learning tooling and infrastructure.

Apply below