Senior MLOps Engineer: Drive Production AI in Biomedicine in London

Senior MLOps Engineer: Drive Production AI in Biomedicine in London

London Full-Time 55000 - 70000 Β£ / year (est.) No working from home possible
Boehringer Ingelheim GmbH

At a Glance

  • Tasks: Manage AI model deployment and ensure operational excellence in biomedicine.
  • Company: Join Boehringer Ingelheim, a leader in biopharmaceutical innovation.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on cutting-edge technology.
  • Why this job: Be at the forefront of AI in healthcare and make a real difference.
  • Qualifications: Experience in MLOps and strong collaboration skills required.

The predicted salary is between 55000 - 70000 Β£ per year.

Boehringer Ingelheim GmbH is seeking a Senior MLOps Engineer to join the AI Enablement team in London. The role focuses on ensuring the models from the AI Accelerator transition from development to production with reliability and operational excellence.

You will manage end-to-end deployment, monitoring, and lifecycle of models, collaborating closely with ML engineers. This is a hybrid role requiring about 3 days in the office weekly.

Senior MLOps Engineer: Drive Production AI in Biomedicine in London employer: Boehringer Ingelheim GmbH

Boehringer Ingelheim GmbH is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration within the AI Enablement team in London. Employees benefit from a hybrid working model, competitive remuneration, and ample opportunities for professional growth in the rapidly evolving field of biomedicine, making it a rewarding place to advance your career while contributing to meaningful advancements in healthcare.

Boehringer Ingelheim GmbH

Contact Details:

Boehringer Ingelheim GmbH Recruitment Team

We think you need these skills to ace Senior MLOps Engineer: Drive Production AI in Biomedicine in London

MLOps
Model Deployment
Model Monitoring
Lifecycle Management
Collaboration with ML Engineers
Reliability Engineering
Operational Excellence