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We're looking for an exceptional Benchmarking & Strategy Manager to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly ...

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Benchmarking information

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How much do benchmarking jobs pay per year?

As of Aug 12, 2026, the average yearly pay for benchmarking in the United States is $80,386.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,000.00 and $87,000.00 per year, depending on experience, location, and employer.

How does a Benchmarking Analyst typically collaborate with other departments to drive performance improvements?

Benchmarking Analysts frequently work cross-functionally, partnering with teams such as operations, finance, and quality assurance to collect data and compare organizational performance against industry standards. They facilitate workshops, share insights, and help identify actionable areas for improvement. This collaborative approach ensures that recommendations are tailored to each department's unique challenges and that initiatives are widely supported and successfully implemented.

What are the key skills and qualifications needed to thrive as a Benchmarking Analyst, and why are they important?

To thrive as a Benchmarking Analyst, you need strong analytical skills, attention to detail, and a background in business, statistics, or related fields. Familiarity with data analysis tools like Excel, SQL, or benchmarking software, as well as certifications such as Six Sigma, are often valuable. Excellent communication, critical thinking, and problem-solving abilities help you interpret data and present actionable insights to stakeholders. These skills are crucial for driving performance improvements and maintaining competitiveness by accurately comparing organizational practices against industry standards.

What is the difference between Benchmarking vs Data Analyst?

AspectBenchmarkingData Analyst
Required credentialsOften requires business or industry-specific certifications, degrees in business, economics, or related fieldsTypically requires degrees in statistics, mathematics, or computer science; certifications like CAP or Microsoft Data Analyst
Work environmentPrimarily in corporate, manufacturing, or consulting settings focusing on performance comparisonIn various industries, working with data sets, reporting, and data visualization tools
Employer and industry usageUsed by organizations to improve processes by comparing against best practicesUsed across industries for data analysis, reporting, and decision-making support

While Benchmarking focuses on comparing organizational performance to industry standards, Data Analysts interpret data to inform business decisions. Both roles require analytical skills but serve different strategic purposes within organizations.

What is benchmarking?

Benchmarking is the process of comparing a company's products, services, or processes against those of leading organizations in the industry or best practices from other industries. The goal is to identify areas where improvements can be made to increase efficiency, quality, or competitiveness. Benchmarking often involves collecting data, analyzing performance metrics, and implementing changes based on findings. This strategic approach helps organizations stay competitive and continuously improve their operations.
More about Benchmarking jobs
What cities are hiring for Benchmarking jobs? Cities with the most Benchmarking job openings:
What states have the most Benchmarking jobs? States with the most job openings for Benchmarking jobs include:
Infographic showing various Benchmarking job openings in the United States as of August 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 83% Physical, 7% Hybrid, and 10% Remote job distribution, with an average salary of $80,386 per year, or $38.6 per hour.

Principal Engineer - Perf and Benchmarking

CoreWeave

Bellevue, WA • On-site

$206K - $333K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago


CoreWeave rating

9.8

Company rating: 9.8 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 223 rated it services


Job 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.
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, 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.
  • 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.
  • 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.
  • 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).
  • 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.

Who you are
  • 10+ years building distributed systems or HPC/cloud services, with deep expertise on large-scale ML training or similar high-performance workloads.
  • Proven track record of architecting or building planet-scale data systems (e.g., telemetry platforms, observability stacks, cloud data warehouses, large-scale OLAP engines).
  • Deep 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).
  • 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 (thousands of GPUs).
  • Publications/talks on ML performance, latency engineering, or large-scale benchmarking methodology.

The 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).
What We Offer
The 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.
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
  • Flexible Spending Account
  • Health Savings Account
  • Tuition Reimbursement
  • Ability to Participate in Employee Stock Purchase Program (ESPP)
  • Mental Wellness Benefits through Spring Health
  • Family-Forming support provided by Carrot
  • Paid Parental Leave
  • Flexible, full-service childcare support with Kinside
  • 401(k) with a generous employer match
  • Flexible PTO
  • Catered lunch each day in our office and data center locations
  • A casual work environment
  • A work culture focused on innovative disruption

California Applicants
California Consumer Privacy Act
Equal Opportunity & Accommodations
CoreWeave 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.
As 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: careers@coreweave.com.
Export Control Compliance
This 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. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

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