Senior Software Engineer - Perf and Benchmarking

About this role 

We’re looking for a Senior Engineer for CoreWeave’s Benchmarking & Performance team. You will have an integral part in our planet-scale performance data warehouse: Ingesting, storing, transforming and analyzing performance events in all the data centers across our global infrastructure. You will also aid us in achieving industry-leading end-to-end performance benchmarking publications such as MLPerf.

You will be an owner who leads designs, raises engineering standards, and delivers measurable improvements to latency, throughput, and reliability across multiple services. You’ll partner with product, orchestration, and hardware teams to evolve our Kubernetes-native platform and meet strict P99 SLAs at scale.

What you’ll do

• Develop and enhance Kubernetes-native benchmarking services that measure latency, throughput, jitter, and cost-per-request across CoreWeave’s compute stack.
• Contribute to implementing and maintaining benchmarking workflows for end-to-end MLPerf Training and Inference runs, including workload setup, cluster configuration, and result validation.
• Participate in design discussions and contribute to architecture decisions within the team.
• Break down engineering tasks into clear milestones and deliver reliable, high-quality code.
• Collaborate with teammates to maintain reproducible, well-documented benchmarking processes.
• Provide constructive code reviews and share best practices with peers.
• Mentor junior engineers; review cross-team designs and elevate coding/testing standards.
• Help ensure reproducible, well-documented benchmarking processes.
  
  

Who you are

• 3–5 years of experience building distributed systems, high-performance computing components, or cloud services.
• Strong programming skills in Python or Go (C++ a plus) with understanding of networked systems and performance fundamentals.
• Hands-on experience with Kubernetes in production environments plus familiarity with CI/CD and observability tools (e.g., Prometheus, Grafana, OpenTelemetry).
• Exposure to performance-critical GPU systems (CUDA, NCCL, NVLink/PCIe, memory bandwidth) or model-serving stacks (llm-d, vLLM, TensorRT-LLM, Megatron-LM).
• Effective communicator comfortable working cross-functionally.
  
  

Nice to have

• Experience with time-series databases, LSM-based storage engines, or custom data pipelines.
• Familiarity with MLPerf or other large-scale benchmarking frameworks.
• Contributions to OSS projects such as llm-d, vLLM or PyTorch.
• Exposure to benchmarking GPU clusters or multi-region environments.
• Background working with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies.

The base salary range for this role is $182,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).