Making AI run fast on any hardware. Backed by Y Combinator and Felicis.
About the role
Research and build faster kernels for AI workloads. You'll work closely with the compiler team, investigate performance bottlenecks, and take optimizations through correctness checks, benchmarking, and execution on real hardware. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Hands-on experience developing GPU kernels
More about this role
- Hands-on experience developing GPU kernels.
- Prior work on kernel autoresearch frameworks is a very strong positive .
- Experience with ML compilers is a strong positive , but not required.
- Hardware performance analysis, memory hierarchies, parallel execution, and benchmarking.
- CUDA, Triton, GPU instruction sets, or compiler systems such as MLIR/LLVM and PyTorch backends.
- Rust, open-source compiler contributions, or work on other accelerators.
No degree requirement. Researchers, recent PhDs, and candidates with substantial relevant projects are welcome.
Luminal (YC S25) builds an AI compiler and serving stack that optimizes models for faster, more efficient execution across accelerators. We're a small team working in person in San Francisco.
Research and build faster kernels for AI workloads. You'll work closely with the compiler team, investigate performance bottlenecks, and take optimizations through correctness checks, benchmarking, and execution on real hardware.
- Agent-driven systems that write, test, and improve kernels.
- Automated kernel research and search-based performance optimization.
- More efficient execution for inference and LLM training.
Candidates who...
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