Founding GPU Compiler Engineer

San Francisco Tensor Company

San Francisco (CA)

On-site

USD 285,000 - 315,000

Full time

14 days+

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Benefits offered by this job

Relocation assistance
Bonus
Equity

Job summary

San Francisco Tensor Company is looking for a Founding GPU Compiler Engineer to be instrumental in building the core compilation infrastructure for AI workloads. This role involves designing compilation pipelines and optimizing for various GPU architectures.

Join a passionate team dedicated to redefining software efficiency and collaborate closely with ML researchers. The position is located in San Francisco and offers a competitive salary range of $285,000 - $315,000 plus benefits.

Qualifications

  • Deep experience with compiler infrastructure (LLVM, MLIR, or similar).
  • Strong background in GPU architecture and low-level optimization (CUDA, ROCm, or equivalent).
  • Proven track record of building production‑grade compiler infrastructure.

Responsibilities

  • Design and implement the main compilation pipeline from StableHLO to executable binaries.
  • Develop backend code generation for multiple targets like NVIDIA and AMD.
  • Work closely with ML researchers to optimize workloads.

Skills

Compiler infrastructure experience
GPU architecture knowledge
Systems programming in C++ or Rust

Tools

LLVM
MLIR
CUDA

Job description

About SF Tensor

At The San Francisco Tensor Company, we believe the future of AI and high-performance computing depends on rethinking the entire software and infrastructure stack. Today's developers face bottlenecks across hardware, cloud, and code optimization that slow progress before ideas can reach their full potential. Our mission is to remove those barriers and make compute faster, cheaper, and universally portable.


We are building a Kernel Optimizer that automatically transforms code into its most efficient form, combined with Tensor Cloud for adaptive, cross-cloud compute and Emma Lang, a new programming language for high-performance, hardware-aware computation. Together, these technologies reinvent the foundations of AI and HPC.


SF Tensor is proudly backed by Susa Ventures and Y Combinator, as well as a group of angels including Max Mullen and Paul Graham as well as founders and executives of NeuraLink, Notion and AMD. We are partnering with researchers, engineers, and organizations who share our belief that the next breakthroughs in AI require breakthroughs in compute.


About the Role

We're hiring a Founding GPU Compiler Engineer to build the core compilation infrastructure for our AI compiler. That means taking models from PyTorch, JAX, and TensorFlow and turning them into highly optimized binaries for large-scale AI pre-training.


You'll own the entire compiler stack, from ingesting StableHLO all the way to backend code generation, and you'll work across targets like NVIDIA, AMD, Trainium, and TPU. You'll help shape our architecture, tooling, and overall engineering culture from the very beginning.


What You’ll Do


  • Design and implement the main compilation pipeline, from StableHLO to executable GPU and host binaries

  • Build and extend MLIR dialects and passes to optimize AI workloads

  • Develop backend code generation for multiple targets (NVIDIA PTX/SASS, AMD GCN/RDNA, Trainium, TPU)

  • Implement classic compiler optimizations customized for large-scale training (fusion, tiling, memory planning, scheduling)

  • Build search‑based compiler infrastructure to explore different optimization options

  • Create hybrid codegen paths for cases where direct MLIR lowering isn’t practical

  • Set up testing, benchmarking, and performance regression systems

  • Work closely with ML researchers to understand workload characteristics and find optimization opportunities


What We’re Looking For


  • Deep experience with compiler infrastructure (LLVM, MLIR, or similar)

  • Strong background in GPU architecture and low-level optimization (CUDA, ROCm, or equivalent)

  • Hands‑on experience with at least one of: PTX/SASS, GCN/RDNA assembly, or other GPU ISAs

  • Familiarity with ML compiler stacks (XLA, TVM, Triton, torch.compile, or similar)

  • Solid systems programming skills in C++ and/or Rust

  • Proven track record of building production‑grade compiler infrastructure


Nice to Have


  • Background in distributed systems or multi-device compilation

  • Contributions to open-source compiler projects

  • Experience with autotuning or search-based optimization

  • Familiarity with large‑scale training infrastructure

  • Experience with (Stable)HLO


Why Join Us

You’ll be one of the first engineers defining how we compile and optimize AI workloads. It's a rare chance to build a compiler stack from the ground up, with a direct impact on the efficiency of large-scale AI training.


We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our San Francisco office.


The base salary range for this full-time position is $285,000 - $315,000 + bonus + equity + benefits.

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