MTS, Research Engineer

📋 Description Conduct open-ended research on model architectures and training objectives. Reproduce and extend state-of-the-art results from papers. Build and scale distributed training infrastructure for large GPU clusters. Bridge science and engineering by turning ideas into robust code. Collaborate cross-functionally with researchers to unblock experiments via tooling and optimization. 🎯 Requirements Strong programming skills in Python, C++, or Rust; write clean, maintainable code. Deep knowledge of ML frameworks: PyTorch, JAX, or TensorFlow. Experience with large distributed systems and parallel computing (CUDA, NCCL, MPI). Strong foundation in linear algebra, calculus, probability, and statistics. Proven track record implementing complex deep learning algorithms from scratch. Nice-to-have: Master’s or PhD in CS/ML or related field (or equivalent industry experience). 🎁 Benefits Solve hard problems at the AI infrastructure frontier. Build cutting-edge tech that impacts AI globally. Ownership and impact in a fast-growing startup. Equity in a fast-growing startup. Comprehensive benefits package. Keystone AI is an equal-opportunity employer.