Senior Data & MLOps Engineer - AI Reliability Platform

CoreWeave; Greater London; On-site; GBP 120,000 - 190,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Pension

Life Assurance 4x Salary

Critical Illness Cover

Employee Assistance Programme

Tuition Reimbursement

Innovative disruption culture

Job summary

CoreWeave is recruiting a Senior Data & MLOps Engineer to design and scale the GPU Intelligence Platform infrastructure, building pipelines for data, features, and model training while delivering insights for system health and optimization.

You will transition prototypes to production across a fleet, focusing on scalable distributed services, separating real-time from offline processing, and dynamic resource management based on load and data frequency.

Qualifications

• 7+ years of experience in data engineering, distributed systems, MLOps, or infrastructure ML roles in production environments.
• Experience building high-throughput streaming or telemetry pipelines (e.g., Kafka, Pulsar, Kinesis, or equivalent).
• Strong experience designing time-series feature pipelines and operating large-scale observability systems.
• Experience building and maintaining feature stores and ensuring offline/online feature parity.
• Hands‑on experience deploying ML models to production, including versioning, monitoring, rollback, and drift detection.
• Experience designing scalable microservices deployed in Kubernetes-based environments.
• Strong proficiency in Python and at least one systems language (Go, Rust, or C++).
• Experience working with distributed compute or training systems (e.g., NCCL, PyTorch Distributed, Spark, Ray, Slurm).
• Familiarity with GPU telemetry systems such as NVML or DCGM and hardware‑level monitoring concepts.
• Demonstrated experience scaling systems from Proof‑of‑Concept to production‑grade, fleet‑level deployments.

Responsibilities

• Design and implement scalable data ingestion pipelines.
• Build feature processing and baseline computation systems.
• Productionize models for prediction and detection.
• Develop and operate low-latency service and robust offline workflows.
• Architect horizontally scalable services with clear separation between components, leveraging orchestration for distribution.
• Implement monitoring and feedback loops for continuous model and signal improvement.
• Collaborate with Platform teams to integrate operational signals into monitoring and diagnostics.
• Implement a scalable solution for mitigation and structured analysis.

Skills

Data engineering

Distributed systems

MLOps

Python

Go

Rust

C++

Kubernetes

Streaming pipelines

Observability

Tools

Kafka

Pulsar

Kinesis

Job description

CoreWeave is recruiting a Senior Data & MLOps Engineer to design and scale the GPU Intelligence Platform infrastructure, building pipelines for data, features, and model training while delivering insights for system health and optimization.

You will transition prototypes to production across a fleet, focusing on scalable distributed services, separating real-time from offline processing, and dynamic resource management based on load and data frequency.