Senior Data & MLOps Engineer
CoreWeave — London, England, United Kingdom · In-Person · Senior
Role description
Role Overview
The Data Science team is focused on developing an advanced reliability platform. This system covers various aspects of data processing and analysis, including data intake, deriving meaningful metrics, identifying unusual patterns, predicting potential issues, finding slow processes in distributed systems, and using automated analysis to determine causes. As a Senior Data & MLOps Engineer, you will design and scale the infrastructure supporting the GPU Intelligence Platform.
What You Will Do
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, and architect horizontally scalable services with clear separation between components.
Why It Might Be a Fit
You love building systems that turn raw infrastructure telemetry into actionable intelligence, are curious about distributed systems failure modes, GPU performance pathologies, and reliability engineering at scale, and enjoy designing platforms that protect uptime, revenue, and customer trust through proactive systems thinking.
Requirements
- 7+ years of experience in data engineering, distributed systems, MLOps, or infrastructure ML roles in production environments
- Proven experience building high-throughput streaming or telemetry pipelines
- 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
- Familiarity with GPU telemetry systems such as NVML or DCGM and hardware-level monitoring concepts
Benefits
- Family-level Medical Insurance
- Family-level Dental Insurance
- Generous Pension Contribution
- Life Assurance at 4x Salary
- Critical Illness Cover
- Employee Assistance Programme
- Tuition Reimbursement