Engineering Manager - Inference Performance

San Francisco · New York · Full-time · Hybrid · Posted Oct 7, 2026

At a glance

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 https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.

The Engineering Manager for Inference Performance will lead and grow a team focused on optimizing AI workloads for speed and efficiency on GPUs. This is a hands-on technical leadership role that involves setting the technical roadmap, mentoring engineers, and driving the productionization of advanced inference techniques.

Lead, mentor and grow a team of inference performance engineers through regular 1:1s, clear feedback, career development and performance reviews.
Hire top GPU and inference engineering talent, and build a strong, collaborative team culture as the runtime team scales.
Own the technical roadmap and execution for runtime performance work, balancing customer needs, new model launches and long-term platform investments.
Stay close to the technical work by reviewing designs, guiding profiling and optimization efforts, and helping the team reason from first principles.
Drive the productionization of inference techniques such as quantization, speculative decoding, KV-cache reuse, chunked prefill and custom scheduling.
Turn performance wins into measurable outcomes: tokens per GPU-hour, utilization, latency and cost.
Help the team bring up and tune new model architectures on new hardware quickly.
Partner with Infrastructure, Inference Platform, Kernels, Model APIs and customer-facing teams to set priorities, coordinate launches and ship wins.
Set high standards for engineering quality, benchmarking, operational excellence and incident response.

Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field.
Experience managing engineers, including hiring, mentoring, giving feedback and running performance reviews.
Experience leading or closely supporting GPU optimization teams in training, inference or recommendation systems.
Strong technical depth in GPU workloads, with a solid understanding of GPU architecture and performance tradeoffs.
Familiarity with ML libraries such as PyTorch, TensorRT or TensorRT-LLM.
A track record of driving roadmaps and shipping complex technical projects with a team.
Clear written and verbal communication, including the ability to align stakeholders across teams.

Familiarity with inference engines such as vLLM, SGLang or TensorRT-LLM.
Experience with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching) in production.
Experience with GPU kernels (CUDA, Triton, CUTLASS, or similar).
Experience scaling a team through rapid growth at a startup.
A background as a hands-on performance or systems engineer before moving into management.

Competitive compensation, including meaningful equity
100% coverage of medical, dental, and vision insurance for employee and dependents (U.S. only)
Flexible PTO policy including company wide Winter Break
Paid parental leave
Fertility and family-building stipend through Carrot
Company-facilitated 401(k) (U.S. only)
Exposure to a variety of ML startups

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