Machine Learning Engineer (Reinforcement Learning)

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.

Responsibilities

• 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.

Requirements

• 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.

Compensation

• 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