Machine Learning Performance Engineer

We are recruiting on behalf of an ambitious new startup founded by an exceptional team of ex-big tech researchers and engineers. Based between London and SF, they’ve recently raised over $15M in pre-seed funding from world-class investors and are building a technical founding team to take on some of the hardest and most exciting challenges in AI today.

The company is still in stealth, but their focus is bold and clear: pushing the boundaries of foundational model architecture, efficient training at scale, and real-world deployment of intelligent agents. This is a rare opportunity to join early and shape the technical DNA of a company that is making major mark in the future of AI/AGI.

What We’re Looking For

There’s no checklist, but you’ll likely thrive in this role if you have:

Technical Experience

• Strong engineering skills in Python, C++, or Rust
• Proven experience with GPU performance engineering: CUDA, PTX/SASS, Tensor Cores, memory hierarchy, warp-level primitives
• Familiarity with ML frameworks like PyTorch, and their internals
• Proficiency in profiling and debugging tools like NSight, CUDA GDB, nvprof, NSight Compute
• Deep knowledge of Triton, cuDNN, cuBLAS, CUTLASS, CUB, or similar libraries
• Experience optimising across the stack: from kern...