Senior MLOps Engineer: GPU AI Reliability & Scale

Senior MLOps Engineer: GPU AI Reliability & Scale

Full-Time 72000 - 88000 Β£ / year (est.) No working from home possible
CoreWeave

At a Glance

  • Tasks: Design and scale GPU Intelligence Platform infrastructure while building data pipelines and productionising models.
  • Company: CoreWeave, a leader in GPU AI technology with a focus on innovation.
  • Benefits: Attractive salary, flexible work options, and opportunities for professional growth.
  • Other info: Be part of a forward-thinking company with a collaborative culture.
  • Why this job: Join a cutting-edge team to enhance AI reliability and scalability in a dynamic environment.
  • Qualifications: Experience in MLOps, Kubernetes, and strong problem-solving skills.

The predicted salary is between 72000 - 88000 Β£ per year.

Core Weave is looking for a Senior Data & MLOps Engineer to design and scale the GPU Intelligence Platform infrastructure.

You will build data pipelines, feature processing, and productionize models across a distributed fleet while separating real-time and batch workloads.

You will deploy scalable services with Kubernetes, apply monitoring, and drive drift detection and diagnostics across teams to improve system health and performance.

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Senior MLOps Engineer: GPU AI Reliability & Scale employer: CoreWeave

CoreWeave is an exceptional employer, offering a dynamic work environment in Greater London where innovation meets reliability. With comprehensive benefits such as family-level medical and dental insurance, pension contributions, and tuition reimbursement, employees are supported both personally and professionally. The company fosters a culture of growth and collaboration, ensuring that every Data Centre Technician has the opportunity to develop their skills while contributing to cutting-edge data centre operations.

CoreWeave

Contact Details:

CoreWeave Recruitment Team

We think you need these skills to ace Senior MLOps Engineer: GPU AI Reliability & Scale

MLOps
GPU Infrastructure Design
Data Pipeline Development
Feature Processing
Model Productionisation
Kubernetes
Monitoring