Principal Engineer - Perf and Benchmarking

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. About this role We’re looking for a Principal Engineer to be the technical lead of CoreWeave’s Benchmarking & Performance team. You will be responsible for 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 be an integral part of achieving industry-leading end-to-end performance benchmarking publications: If MLPerf (Training & Inference), Working closely with NVIDIA (Megatron-LM, TensorRT-LLM & DGX cloud) and the open-source community (llm-d, vLLM and all popular ML frameworks) speak to you, come help us demonstrate CoreWeave’s performance reliability leadership in the field. What you’ll do Strategy & Leadership - Define the multi-year benchmarking strategy and roadmap; prioritize models/workloads (LLMs, diffusion, vision, [... source excerpt omitted ...] hServe), and distributed training frameworks (PyTorch FSDP/DeepSpeed/Megatron-LM). Proficient with Kubernetes and ML control planes; familiarity with SUNK, Kueue, and Kubeflow in production environments. Excellent communicator able to interface with executives, customers, auditors, and OSS communities. Nice to have Experience with time-series databases, log-structured merge trees (LSM), or custom storage engine development. Experience running MLPerf submissions (Inference and/or Training) or equivalent audited benchmarks at scale. Contributions to MLPerf, Triton, vLLM, PyTorch, KServe, or similar OSS projects. Experience benchmarking multi-region fleets and large clusters (t [... source excerpt omitted ...] the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Fl