3 months ago
Base Salary
$182k - $242k/yr
Responsibilities
- Author, profile, and optimize CUDA kernels for GEMMs, attention, MoE routing, quantization, KV-cache operations, and fused epilogues in LLM inference
- Tune GPU execution using tensor cores, occupancy, memory coalescing, shared-memory and register usage, and compute/data-movement overlap
- Use kernel-authoring DSLs and compilers to prototype and ship high-performance kernels
- Build reproducible microbenchmarks and roofline analyses and validate end-to-end latency and throughput gains across model-serving stacks
- Implement and maintain MLPerf Inference and Training benchmarking workflows, including workload setup, cluster configuration, runbooks, and result validation
- Lead design reviews, drive team architecture, and decompose multi-service work into milestones
- Mentor junior engineers, review cross-team designs, and improve coding and testing standards
- Maintain reproducible and well-documented benchmarking and kernel-optimization processes
Requirements
- At least 5 years of experience building high-performance computing, GPU/accelerator software, or performance-critical systems
- Required hands-on CUDA experience, including writing and optimizing custom kernels and fluency with the CUDA programming and memory model
- Deep understanding of GPU architecture and performance, including tensor cores, warp and occupancy tuning, memory hierarchy and bandwidth, NVLink, PCIe, and Nsight profiling
- Strong C++ and Python programming skills with comfort writing and reading low-level, performance-sensitive code
- Familiarity with vLLM, TensorRT-LLM, llm-d, SGLang, and inference-dominant kernels
- Strong communication and cross-functional collaboration skills
- Preferred experience with Triton or Mojo for custom GPU kernel authoring
- Preferred experience with CuTe DSL, JAX, Pallas, HIP, ROCm, NCCL, Google TPUs, Meta MTIA, KNYFE, Block DSL, Kubernetes, SUNK, Slurm, MLPerf, vLLM, SGLang, PyTorch, Triton, or CUTLASS
- Experience with MLPerf submissions or similar large-scale audited benchmarks is preferred
- Contributions to open-source projects such as vLLM, SGLang, PyTorch, Triton, or CUTLASS are preferred
- Must meet applicable US export-control eligibility requirements for access to controlled information
Benefits
- Medical, dental, and vision insurance fully paid by CoreWeave for US-based employees
- Company-paid life insurance and voluntary supplemental life insurance
- Short- and long-term disability insurance
- Flexible Spending Account and Health Savings Account
- Tuition reimbursement
- Employee Stock Purchase Program participation
- Mental wellness benefits through Spring Health
- Family-forming support through Carrot
- Paid parental leave
- Flexible, full-service childcare support through Kinside
- 401(k) with an employer match
- Flexible PTO
- Catered lunch at office and data center locations
- Casual work environment
- Export-controlled information access requirements apply, subject to US export regulations
Tech Stack
Categories
About CoreWeave
CoreWeave provides a GPU-accelerated cloud for AI training and inference, VFX, and rendering, with bare-metal instances, Kubernetes orchestration, and managed services to scale workloads. It sells on-demand and reserved capacity to AI labs, startups, and enterprises, and offers SaaS tools and hands-on support for deployment. Founded in 2017 and headquartered in New York, it is publicly traded on Nasdaq under the ticker CRWV.