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Baseten

Runs AI models for production software

Software Engineer - GPU Kernels

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Strong understanding of GPU architecture and programming paradigms, including memory hierarchy (global, shared, registers, L1/L2 cache), thread/block/grid organization, synchronization techniques, and race-condition mitigation.
  • Proficiency in C++ and GPU performance profiling tools.
  • Knowledge of the CUDA C++ API, memory access patterns and bandwidth optimization, numerical precision and quantization strategies, and modern GPU features such as tensor cores and asynchronous operations.

Responsibilities

  • Design and implement high-performance GPU kernels for key machine-learning operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing.
  • Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques.
  • Apply performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap.
  • Implement features such as quantization (FP8/FP4), sparsity, and compute/communication overlap.
  • Identify and resolve performance bottlenecks using Nsight Systems, Nsight Compute, and Torch Profiler.
  • Collaborate with research teams to productionize theoretical advancements.
  • Contribute to internal and open-source GPU libraries.
  • Present technical contributions at industry conferences such as NVIDIA GTC and AWS re:Invent.

Desired Qualifications

  • Experience with Transformer models and attention optimization, such as Flash Attention.
  • Familiarity with GPU kernel libraries including Cutlass, Triton, Thrust, and CUB.
  • Background in GEMM tuning and distributed or multi-GPU compute.
  • Contributions to open-source GPU projects.
  • Research publications or conference presentations on GPU performance.

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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