CoreWeave

AI

SeniorSoftwareEngineer-PerfandBenchmarking

$182–242k Bellevue, Washington, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Software Engineer - Perf and Benchmarking at CoreWeave. Skills: distributed systems, high-performance computing, cloud services, Python, Go, Kubernetes, CI/CD, observability, GPU systems, benchmarking. review cross-team designs. elevate coding/testing standards”

What You'll Achieve.

build and scale AI with confidence; accelerate breakthroughs and turn compute into capability

Industry & Context.

AI
Eligibility Requirements

Access to export controlled information, Must be a U. S. person (U. S. citizen or national, U. S. lawful permanent resident, refugee, or asylee) or eligible to access export controlled information without authorization or obtain required authorization.

What They're Looking For.

Must Have

3–5 years of experience building distributed systems, high-performance computing components, or cloud services, programming skills in Python or Go, understanding of networked systems and performance fundamentals, Hands-on experience with Kubernetes in production environments, familiarity with CI/CD and observability tools (e. g. , Prometheus, Grafana, OpenTelemetry), 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

What You'll Do.

review cross-team designs

elevate coding/testing standards

well-documented benchmarking processes

How You'll Work.

Team & Collaboration

working cross-functionally; review cross-team designs; Teams also gather quarterly to support collaboration

Communication Scope

Effective communicator

Full 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 Senior Engineer for CoreWeave’s Benchmarking 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

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