Engineering Manager, GPU Kernel Engineering

Stack

Responsibilities

• ▹Lead, grow, and mentor a team of GPU kernel engineers; own hiring, performance, and career development
• ▹Set 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 the broader inference stack strategy
• ▹Drive cross-functional collaboration between the kernel team and Model Performance, Capacity, and Infrastructure teams
• ▹Establish and maintain a high technical bar for kernel quality, performance, and correctness
• ▹Review kernel designs and implementations with enough depth to give meaningful feedback on GPU architecture, memory hierarchy tradeoffs, and optimization strategies
• ▹Guide the team's approach to profiling and bottleneck identification using tools like Nsight Systems, Nsight Compute, and Torch Profiler
• ▹Stay current on the NVIDIA GPU ecosystem (Hopper, Blackwell, and beyond) and translate architectural advancements into team priorities
• ▹Build the processes that allow a highly technical, distributed team to ship with velocity and rigor
• ▹Represent the kernel team's work to senior leadership and external audiences, including industry conferences
• ▹Contribute to Baseten's open-source GPU library presence and technical brand

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 — having written and shipped production CUDA kernels, and able to credibly engage with the 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

Soft skills

What we offer

• ▹Competitive compensation, including meaningful equity
• ▹100% coverage of medical, dental, and vision insurance for employee and dependents
• ▹Flexible PTO policy including company-wide Winter Break (offices closed from Christmas Eve to New Year's Day)
• ▹Paid parental leave
• ▹Fertility and family-building stipend through Carrot
• ▹Company-facilitated 401(k)
• ▹Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities

About the company

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, Baseten enables companies operating at the frontier of AI to bring cutting-edge models into production. The company is growing quickly and recently raised a $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital.