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Baseten

Runs AI models for production software

Engineering Manager - Inference Performance

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • A 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 machine learning 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.

Responsibilities

  • Lead, mentor, and grow a team of inference performance engineers through regular one-on-ones, 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 about where time and memory go.
  • 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, including tokens per GPU-hour, utilization, latency, and cost.
  • Help the team bring up and tune new model architectures on new hardware quickly, often in the same week they are released.
  • 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.

Desired Qualifications

  • Familiarity with inference engines such as vLLM, SGLang, or TensorRT-LLM.
  • Experience with LLM optimization techniques, such as quantization, speculative decoding, or continuous batching, in production.
  • Experience with GPU kernels, including 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.

About the Company

Baseten

Runs AI models for production software

Baseten runs AI models for software companies that need fast, reliable responses inside their products, from text generation to speech and image processing. Its Inference Stack combines optimized model runtimes with infrastructure that deploys, serves, and monitors custom or open models in production. Teams package models with its open source Truss tool, while Model APIs let developers test ready-to-use models and Training runs jobs that adapt models to their own data. Customers pay for computing time or tokens processed, with negotiated plans for larger deployments and support needs. Baseten was founded in 2019 and is headquartered in San Francisco.

Company size
201-500
Company stage
Series F
Total funding
$2.1B
Headquarters
San Francisco, CA
Founded
2019

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