MLOps Engineer for AI Accelerator Hardware in Oxford

MLOps Engineer for AI Accelerator Hardware in Oxford

Oxford Full-Time 60000 - 80000 £ / year (est.) No working from home possible
L

At a Glance

  • Tasks: Own and optimise ML pipelines, tooling, and production deployments for cutting-edge AI models.
  • Company: Lumai Limited, a pioneer in 3D optical compute technology.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Be part of a dynamic environment with significant impact on AI advancements.
  • Why this job: Join a groundbreaking team and shape the future of AI technology.
  • Qualifications: Experience in MLOps, strong collaboration skills, and a passion for AI.

The predicted salary is between 60000 - 80000 £ per year.

Lumai Limited is building a breakthrough AI accelerator for data centers using 3D optical compute.

We seek a senior MLOps Engineer to own end-to-end ML pipelines, tooling, and production deployments for models from research to silicon-validated production.

In this high-ownership role, you’ll collaborate with ML researchers, compiler engineers, and hardware architects to optimize model-to-chip workflows, instrument deployments, and maintain CI/CD for ML across on-prem and cloud environments.

#J-18808-Ljbffr

MLOps Engineer for AI Accelerator Hardware in Oxford employer: Lumai Limited

At Lumai Limited, we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to take ownership of their projects. As an MLOps Engineer, you will have the unique opportunity to work at the forefront of AI technology in a collaborative environment, with ample opportunities for professional growth and development. Our commitment to cutting-edge research and a supportive team atmosphere makes Lumai an exceptional place to advance your career while contributing to groundbreaking advancements in AI hardware.

L

Contact Details:

Lumai Limited Recruitment Team

We think you need these skills to ace MLOps Engineer for AI Accelerator Hardware in Oxford

MLOps
End-to-End ML Pipelines
Tooling for ML
Production Deployments
Collaboration with ML Researchers
Compiler Engineering
Hardware Architecture