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Machine Learning Operations Engineer

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Job Description - Machine Learning Operations Engineer

ML Ops Engineer - Motion Capture Technology | Hybrid (Oxford, UK)

An exciting opportunity has arisen for an ML Ops Engineer to join a world-leading technology company specialising in high-performance motion capture solutions for the entertainment, engineering, and life sciences industries. Their products are widely used in feature films, gaming, commercials, and cutting-edge research in biomechanics, robotics, and beyond.

You'll be part of a collaborative R&D team that's pushing the boundaries of motion capture technology, working in a company with a strong track record of innovation and global impact.

The Role:

You will join the ML Operations team, supporting the development of next-generation motion capture products. The role involves provisioning and maintaining a modern ML Ops stack, which includes data acquisition pipelines, data management systems, and ML model training infrastructure. This stack combines self-managed on-premises systems with cloud-based AWS resources.

As an ML Ops Engineer, you'll have the opportunity to influence technical direction, propose new solutions, and potentially lead projects within the team.

The company offers a hybrid working model, with a head office in a major academic city. There is no on-call expectation outside of core office hours.

Key Responsibilities:

  • Manage and maintain on-premise Kubernetes clusters

  • Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow)

  • Develop scripts and tooling in Python; manage Linux system configurations

  • Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.)

  • Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows

  • Design and deploy robust ML Ops solutions across various technologies

  • Contribute to the technical strategy and suggest improvements to the ML Ops stack

Required Skills and Experience:

  • Solid experience managing on-premise Kubernetes clusters

  • Strong knowledge of Kubeflow or similar ML Ops platforms

  • Proficiency in Python programming, Linux systems, and scripting

  • Experience with AWS services (Cognito, S3, EC2, Lambda, etc.)

  • Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines

  • Ability to design and implement comprehensive ML Ops solutions

Desirable Skills:

  • Background in DevOps with CI/CD experience (e.g., Jenkins)

  • Knowledge of infrastructure-as-code tools (e.g., Ansible)

  • Interest in human motion capture, sports, or animation technologies

  • Familiarity with C++

Benefits Package:

  • Competitive salary

  • 10% company pension contribution

  • 25 days annual leave + bank holidays

  • Life cover

  • Private medical insurance with optical/dental coverage

  • Permanent health insurance

  • Cycle to work scheme

  • Free on-site parking

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