Senior Software Engineer

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

• Build and improve Kubernetes-native benchmarking services that measure latency, throughput, jitter, and cost-per-request across CoreWeave’s compute stack.
• Implement and maintain benchmarking workflows for end-to-end MLPerf Training and Inference runs, including workload setup, cluster configuration, runbooks, and result validation.
• Lead design reviews and drive architecture within the team; decompose multi-service work into clear milestones.
• Mentor junior engineers; review cross-team designs and elevate coding/testing standards.
• Help ensure reproducible, well-documented benchmarking processes.
  
  

Who you are

• 5+ years of experience building distributed systems, high-performance computing, or cloud services.
• Strong coding in Python or Go (C++ a plus) and deep familiarity with networked systems and performance.
• Hands-on experience with Kubernetes at production scale, CI/CD, and observability stacks (Prometheus, Grafana, OpenTelemetry).
• Experience with performance-critical GPU systems (CUDA, NCCL, RDMA, NVLink/PCIe, memory bandwidth) and model-serving stacks (llm-d, vLLM, TensorRT-LLM, Megatron-LM).
• Strong communicator comfortable collaborating with cross-functional teams and external partners.
  
  

Nice to have

• Experience with time-series databases, LSM-based storage engines, or custom data pipelines.
• Experience running MLPerf submissions or similar large-scale audited benchmarks.
• Contributions to OSS projects such as llm-d, vLLM or PyTorch.
• Exposure to benchmarking large GPU fleets or multi-region clusters.
• Experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies.
  
  

Why CoreWeave

Help shape an industry-defining inference platform that enables teams to deploy generative AI and real-time applications at scale. If optimizing tail latency and delivering reliable model serving excites you, this is the place to build.

The base salary range for this role is $139,000 to $204,000. 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).