Senior MLOps Engineer - Deploy, Monitor & Scale ML in London

Senior MLOps Engineer - Deploy, Monitor & Scale ML in London

London Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Affinity Water Limited

At a Glance

  • Tasks: Build and optimise ML deployment pipelines while monitoring model performance.
  • Company: Affinity Water Limited, a leader in operationalising machine learning.
  • Benefits: Competitive salary from £60,000, flexible working, and comprehensive benefits.
  • Other info: Enjoy a supportive environment with opportunities for personal growth.
  • Why this job: Join us to make a real impact in the world of machine learning.
  • Qualifications: Experience in MLOps and strong problem-solving skills.

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

Affinity Water Limited is seeking a Machine Learning Ops Engineer to operationalise ML across the organization on a 24-month FTC. You will build and optimise ML deployment pipelines, monitor model performance, and support ML platforms both on-premise and in the cloud.

The position offers a competitive salary starting from £60,000, flexible working at our Hatfield office, and a comprehensive benefits package that includes a generous pension scheme and wellbeing support.

Senior MLOps Engineer - Deploy, Monitor & Scale ML in London employer: Affinity Water Limited

Affinity Water Limited is an excellent employer that prioritises employee wellbeing and professional growth, offering a competitive salary and a comprehensive benefits package, including a generous pension scheme. With flexible working arrangements at our Hatfield office, we foster a supportive work culture that encourages innovation and collaboration, making it an ideal environment for those looking to make a meaningful impact in the field of machine learning operations.

Affinity Water Limited

Contact Details:

Affinity Water Limited Recruitment Team

We think you need these skills to ace Senior MLOps Engineer - Deploy, Monitor & Scale ML in London

Machine Learning Operations (MLOps)
ML Deployment Pipelines
Model Performance Monitoring
Cloud Platforms
On-Premise Solutions
Optimisation Skills
Technical Support