Engineering
About the role
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products.
Responsibilities
Lead, grow, and mentor a team of GPU kernel engineers; own hiring, performance, and career development
Own technical direction for the kernel roadmap, balancing short-term inference wins with long-term architectural investments
Partner closely with the Chief Scientist, VP Engineering, and peer engineering leads to align kernel work with Baseten's broader inference stack strategy
Drive cross-functional collaboration between the kernel team and Model Performance, Capacity, and Infrastructure teams
Requirements
Proven experience leading a team of GPU or ML systems engineers, with a track record of hiring and developing strong technical talent
Deep personal background in GPU kernel engineering. You have written and shipped production CUDA kernels and can credibly engage with your team's work at a technical level
Strong understanding of GPU architecture fundamentals: memory hierarchy, warp execution, tensor cores, occupancy tradeoffs, and profiling methodology
Experience with NVIDIA GPU architectures (Hopper or Blackwell preferred) and the CUDA ecosystem
Demonstrated ability to set technical direction, prioritize a roadmap, and communicate clearly across engineering and leadership
Nice to have
Hands-on experience with Triton, CUTLASS, or CuTe DSL
Background in LLM inference kernels: attention variants, GEMMs, quantization (FP8/FP4), MoE routing
Open-source contributions to GPU libraries or inference frameworks
Experience presenting technical work at NVIDIA GTC, MLSys, or similar venues