Engineering

Baseten Baseten · Data AI · San Francisco, CA · EPD

Engineering Manager for GPU Kernel Engineering team responsible for writing low-level CUDA code to optimize Baseten's inference stack for speed and cost. This is a player-coach role requiring deep hands-on experience in GPU kernel development and team leadership.

What you'd actually do

  1. Lead, grow, and mentor a team of GPU kernel engineers; own hiring, performance, and career development
  2. Set technical direction for the kernel roadmap, balancing short-term inference wins with long-term architectural investments
  3. Establish and maintain a high technical bar for kernel quality, performance, and correctness across the team's output
  4. Review kernel designs and implementations with enough depth to give meaningful feedback on GPU architecture decisions, memory hierarchy tradeoffs, and optimization strategies
  5. Stay current on the NVIDIA GPU ecosystem (Hopper, Blackwell, and beyond) and translate architectural advancements into team priorities

Skills

Required

  • Proven experience leading a team of GPU or ML systems engineers
  • Deep personal background in GPU kernel engineering
  • Strong understanding of GPU architecture fundamentals
  • Experience with NVIDIA GPU architectures
  • Demonstrated ability to set technical direction, prioritize a roadmap, and communicate clearly

Nice to have

  • Hands-on experience with Triton, CUTLASS, or CuTe DSL
  • Background in LLM inference kernels
  • Open-source contributions to GPU libraries or inference frameworks
  • Experience presenting technical work at NVIDIA GTC, MLSys, or similar venues

What the JD emphasized

  • Deep personal background in GPU kernel engineering
  • written and shipped production CUDA kernels
  • Strong understanding of GPU architecture fundamentals
  • Experience with NVIDIA GPU architectures (Hopper or Blackwell preferred)

Other signals

  • GPU kernel engineering
  • CUDA
  • inference stack
  • low-level optimization
  • performance and latency