{"id":1229657,"url":"https://alion.io/job/coreweave-principal-engineer-perf-and-benchmarking","title":"Principal Engineer - Perf and Benchmarking","company":{"id":7348,"name":"CoreWeave","domain":"coreweave.com","url":"https://alion.io/company/coreweave","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":76,"open_postings":72,"ghost_share":0,"stale_share":0.778,"repost_share":0,"time_to_fill_p50_days":61,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States","Bellevue, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":206000,"max":333000,"currency":"USD","period":"year","gross":null,"usd_annual":333000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"CI/CD","optional":false},{"name":"CoreWeave","optional":false},{"name":"Cosign","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"cuDNN","optional":false},{"name":"DeepSpeed","optional":false},{"name":"FSDP","optional":false},{"name":"Grafana","optional":false},{"name":"HPC","optional":false},{"name":"KServe","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Megatron-LM","optional":false},{"name":"NCCL","optional":false},{"name":"NVLink","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Prometheus","optional":false},{"name":"PyTorch","optional":false},{"name":"SLURM","optional":false},{"name":"TensorRT","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"TorchServe","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2025-12-18T22:58:28Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-19T17:50:20Z","board_verified":true,"closed_at":null,"days_open":304,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":304},"description":"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.\nAbout this role \nWe’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.\nYou 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.\nWhat you’ll do\n Strategy & Leadership - Define the multi-year benchmarking strategy and roadmap; prioritize models/workloads (LLMs, diffusion, vision, speech) and hardware tiers. Build, lead, and mentor a high-performing team of performance engineers and data analysts. Establish governance for claims: documented methodologies, versioning, reproducibility, and audit trails.\n Perf Ownership - Lead end-to-end MLPerf Inference and Training submissions: workload selection, cluster planning, runbooks, audits, and result publication. Coordinate optimization tracks with NVIDIA (CUDA, cuDNN, TensorRT/TensorRT-LLM, Triton, NCCL) to hit competitive results; drive upstream fixes where needed.\n Internal Latency & Throughput Benchmarks - Design a Kubernetes-native, repeatable benchmarking service that exercises CoreWeave stacks across SUNK (Slurm on Kubernetes), Kueue, and Kubeflow pipelines. Measure and report p50/p95/p99 latency, jitter, tokens/s, time-to-first-token, cold-start/warm-start, and cost-per-token/request across models, precisions (BF16/FP8/FP4), batch sizes, and GPU types. Maintain a corpus of representative scenarios (streaming, batch, multi-tenant) and data sets; automate comparisons across software releases and hardware generations.\n Tooling & Automation - Build CI/CD pipelines and K8s controllers/operators to schedule benchmarks at scale; integrate with observability stacks (Prometheus, Grafana, OpenTelemetry) and results warehouses. Implement supply-chain integrity for benchmark artifacts (SBOMs, Cosign signatures).\n Cross-functional & Community - Partner with NVIDIA, key ISVs, and OSS projects (vLLM, Triton, KServe, PyTorch/DeepSpeed, ONNX Runtime) to co-develop optimizations and upstream improvements. Support Sales/SEs with authoritative numbers for RFPs and competitive evaluations; brief analysts and press with rigorous, defensible data.\nWho you are\n10+ years building distributed systems or HPC/cloud services, with deep expertise on large-scale ML training or similar high-performance workloads.\nProven track record of architecting or building planet-scale data systems (e.g., telemetry platforms, observability stacks, cloud data warehouses, large-scale OLAP engines).\nDeep understanding of GPU performance (CUDA, NCCL, RDMA, NVLink/PCIe, memory bandwidth), model-server stacks (Triton, vLLM, TensorRT-LLM, TorchServe), and distributed training frameworks (PyTorch FSDP/DeepSpeed/Megatron-LM).\nProficient with Kubernetes and ML control planes; familiarity with SUNK, Kueue, and Kubeflow in production environments.\nExcellent communicator able to interface with executives, customers, auditors, and OSS communities.\nNice to have\nExperience with time-series databases, log-structured merge trees (LSM), or custom storage engine development.\nExperience running MLPerf submissions (Inference and/or Training) or equivalent audited benchmarks at scale.\nContributions to MLPerf, Triton, vLLM, PyTorch, KServe, or similar OSS projects.\nExperience benchmarking multi-region fleets and large clusters (thousands of GPUs).\nPublications/talks on ML performance, latency engineering, or large-scale benchmarking methodology.\nThe base salary range for this role is $206,000 to $333,000. 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). \nWhat We Offer\nThe range we’ve posted represents 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.\nIn 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:\nMedical, dental, and vision insurance - 100% paid for by CoreWeave\nCompany-paid Life Insurance \nVoluntary supplemental life insurance \nShort and long-term disability insurance \nFlexible Spending Account\nHealth Savings Account\nTuition Reimbursement \nAbility to Participate in Employee Stock Purchase Program (ESPP)\nMental Wellness Benefits through Spring Health \nFamily-Forming support provided by Carrot\nPaid Parental Leave \nFlexible, full-service childcare support with Kinside\n401(k) with a generous employer match\nFlexible PTO\nCatered lunch each day in our office and data center locations\nA casual work environment\nA work culture focused on innovative disruption\nCalifornia Applicants\nCalifornia Consumer Privacy Act \nEqual Opportunity & Accommodations\nCoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.\nAs part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: .\nExport Control Compliance\nThis position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. 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