Machine Learning Operations Engineer

White Recruitment Construction; England; Hybrid; GBP 65,000 - 75,000; Full time

Job summary

A leading technology firm in Oxfordshire is seeking a Machine Learning Operations Engineer to enhance their ML capabilities. This hybrid role focuses on managing Kubernetes clusters and integrating ML workflows, offering a salary range of £65,000 – £75,000 and robust benefits including private medical insurance and generous leave. Ideal candidates will possess strong experience in ML and AWS services.

Benefits

10 percent company pension

25 days annual leave plus bank holidays

Life assurance

Private medical insurance including dental and optical

Free on site parking

Qualifications

• Academic background in a relevant field preferred.
• Strong experience managing on premise Kubernetes clusters.
• Proficient in Python and experienced with Linux systems.

Responsibilities

• Maintain and improve ML Ops infrastructure.
• Manage on premise Kubernetes clusters and ML pipelines.
• Integrate ML toolkits into operational workflows.

Skills

Managing on premise Kubernetes clusters

Proficient in Python

Deep knowledge of MLflow or similar

Familiar with AWS services

Experience with ML frameworks

Education

Research Masters level or equivalent experience

Tools

Kubernetes

AWS

PyTorch

Job description

Overview

Role: Machine Learning Operations Engineer
Location: Oxfordshire
Salary: £65,000 – £75,000

This is an exciting opportunity to join a world leading company specialising in motion capture and tracking systems, with products used globally in the entertainment, engineering, and life sciences sectors. My Client are looking for a talented Machine Learning Operations Engineer to support and enhance their cutting edge machine learning capabilities.

The Role

You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure, primarily using AWS.

You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects.

This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours.

Key Responsibilities

• Maintain and improve ML Ops infrastructure
• Manage on premise Kubernetes clusters and ML pipelines
• Integrate ML toolkits into operational workflows
• Collaborate with ML developers to streamline workflows
• Suggest and implement technical improvements and new tools

Required Skills and Experience

• Academic background (research Masters level) or industry experience in a relevant field
• Strong experience managing on premise Kubernetes clusters
• Deep knowledge of Kubeflow or similar systems such as MLflow
• Proficient in Python and experienced with Linux systems
• Familiar with AWS services such as Cognito, S3, EC2 and Lambda
• Experience working with ML frameworks such as PyTorch or Lightning
• Capable of designing and delivering ML Ops solutions across various platforms

Desirable Skills

• Background in DevOps with experience in CI systems such as Jenkins
• Familiarity with infrastructure as code tools such as Ansible
• Interest in human motion capture, sports tech, or animation
• Exposure to C++ is a bonus

Benefits

• £65,000 – £75,000 (DOE)
• 10 percent company pension
• 25 days annual leave plus bank holidays
• Life assurance
• Private medical insurance including dental and optical
• Permanent health insurance
• Cycle to work scheme
• Free on site parking.

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