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Machine Learning Operations Engineer

Yarnton
4 months ago
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Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer – 11328SR

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

If you’re passionate about ML Ops and looking to work on pioneering technology in a growing, innovative environment, we’d love to hear from you.

Apply now to be part of a team shaping the future of motion capture technology

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