Senior AI Benchmarking & Performance Engineer

CoreWeave; Sunnyvale (CA); On-site; USD 182,000 - 242,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with generous employer match

Tuition Reimbursement

Flexible PTO

Catered lunch every day

Job summary

CoreWeave is seeking a Senior Engineer for the Benchmarking & Performance team to own the design and delivery of planet-scale performance data workflows. You will drive latency, throughput, and reliability improvements across multiple services while partnering with product, orchestration, and hardware teams to meet strict P99 SLAs at scale.

You will develop benchmarks and workflows for MLPerf training and inference, contribute to architecture decisions, and mentor junior engineers.

Qualifications

• 3–5 years of distributed systems experience.
• Strong Python or Go programming.
• Production Kubernetes experience.
• Familiarity with CI/CD and observability tools.
• Exposure to GPU systems or model-serving stacks.

Responsibilities

• Develop and enhance Kubernetes-native benchmarking services measuring latency, throughput, jitter, and cost-per-request.
• Implement benchmarking workflows for MLPerf Training and Inference runs, including workload setup and validation.
• Participate in design discussions and architecture decisions.
• Break down tasks into milestones and deliver high-quality code.
• Maintain reproducible benchmarking processes and documentation.
• Provide code reviews and share best practices with peers.
• Mentor junior engineers and elevate coding/testing standards.

Skills

Python

Go

Distributed systems

Kubernetes

CI/CD

Performance tuning

Tools

Prometheus

Grafana

OpenTelemetry

CUDA

NCCL

Megatron-LM

Job description

CoreWeave is seeking a Senior Engineer for the Benchmarking & Performance team to own the design and delivery of planet-scale performance data workflows. You will drive latency, throughput, and reliability improvements across multiple services while partnering with product, orchestration, and hardware teams to meet strict P99 SLAs at scale.

You will develop benchmarks and workflows for MLPerf training and inference, contribute to architecture decisions, and mentor junior engineers.