ML Engineer (Internship and Full-time)

Highlights

• Build infrastructure powering cutting-edge interpretability research.
• Optimize training and inference throughput for novel model architectures.
• Scale experimental pipelines to understand and control large models.

Ideal candidate

A fast-learning engineer passionate about ML infrastructure who thrives translating research ideas into scalable systems and cares deeply about advancing interpretability and model understanding.

Requirements

• Experience in deep learning or related research areas
• Demonstrated exceptional capability in ML infrastructure work
• Previous experience with large-scale pre/post-training infrastructure
• Deep familiarity with PyTorch or JAX, basic familiarity with Triton/TileLang/TK
• Ability to design and orchestrate end-to-end ML pipelines
• Clear verbal and written communication and fast learning ability