Machine Learning Engineer

🚀 Hiring: Member of Technical Staff – Machine Learning

📍 San Francisco | Full-time | Onsite - US Citizens only. Visa sponsorship is not available.

We’re hiring exceptional ML researchers and engineers to work on training and optimizing powerful language models.

This is for people who want to push the frontier — whether that means developing new optimization methods, scaling massive training runs, improving post-training and RL, or squeezing every last bit of performance from GPUs.

• We’d love to hear from you if you have experience in areas such as:
• • Large-scale LLM pretraining and training infrastructure
• • Model parallelism and distributed training
• • Monitoring and maintaining large-scale training runs
• • Post-training, reinforcement learning, tool use, or data curation
• • Inference and systems optimization
• • Batching, KV-cache pressure, and long-context optimization
• • Low-level GPU kernel development and software/hardware co-design
• • PyTorch, JAX, CUDA, Triton, C++, CuTE, PTX, or TileLang
• • Contributions to open-source ML systems or research communities
• • Published or independent research in optimization, architectures, training, or post-training

Experience with projects and frameworks such as vLLM, SGLang, Dynamo, MegaKernels, NanoGPT Speedrun, or Marin is highly relevant.

Ideal background:

1+ years in cutting-edge ML/LLM research or engineering, with strong evidence of technical depth through industry experience, academic research, open-source contributions, or exceptional personal projects.

🎯 You don’t need to tick every box. We’re looking for deeply technical, self-motivated people who want to make a meaningful contribution to frontier AI.

📩 Interested? Send me a DM for a confidential conversation.