Senior MLOps Architect for Biomedical AI Platform in London

Senior MLOps Architect for Biomedical AI Platform in London

London Full-Time 81000 - 99000 £ / year (est.) Home office (partial)
Boehringer Ingelheim GmbH

At a Glance

  • Tasks: Lead MLOps architecture for a cutting-edge Biomedical AI platform.
  • Company: Join Boehringer Ingelheim, a leader in innovative healthcare solutions.
  • Benefits: Enjoy a hybrid work model, competitive salary, and career development opportunities.
  • Other info: Collaborate with a passionate team in a dynamic and supportive environment.
  • Why this job: Make a real impact in AI while shaping the future of healthcare.
  • Qualifications: Proven experience in MLOps engineering and strong leadership skills.

The predicted salary is between 81000 - 99000 £ per year.

Boehringer Ingelheim in London seeks a senior leader in MLOps Engineering to own the architecture and standards for the AI Accelerator.

You will drive the end-to-end model lifecycle from training to production deployment and governance.

You will define tooling, platforms and practices that enable large-scale training, experiment tracking, deployment, monitoring and governance, while coaching the growing team.

This is a hybrid role with about 4 days in the office.

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Senior MLOps Architect for Biomedical AI Platform in London employer: Boehringer Ingelheim GmbH

Boehringer Ingelheim is an exceptional employer, recognised as a Top Employer in the UK, offering a supportive work culture that prioritises employee well-being and professional growth. As a Senior ML Engineer in London, you will be at the forefront of biomedical AI, collaborating with leading scientists and engineers to make impactful contributions to human health while enjoying a hybrid work model that promotes work-life balance.

Boehringer Ingelheim GmbH

Contact Details:

Boehringer Ingelheim GmbH Recruitment Team

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We think you need these skills to ace Senior MLOps Architect for Biomedical AI Platform in London

MLOps Engineering
Architecture Design
AI Model Lifecycle Management
Production Deployment
Governance Standards
Tooling and Platform Definition
Experiment Tracking

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