Machine Learning Engineer — Distillation

We’re looking for a Machine Learning Engineer focused on model distillation to help us build smaller, faster, and more efficient models without sacrificing quality. You’ll work at the intersection of research and production—taking cutting-edge techniques and turning them into systems that scale.

This is a hands-on role with real ownership: you’ll design distillation pipelines, run large-scale experiments, and ship models used in production.

Design and implement knowledge distillation pipelines (teacher–student, self-distillation, multi-teacher, etc.)

Distill large foundation models into smaller, faster, and cheaper models for inference

Run and analyze large-scale training experiments to evaluate quality, latency, and cost tradeoffs

Collaborate with research to translate new distillation ideas into production-ready code

Optimize training and inference performance (memory, throughput, latency)

Contribute to internal tooling, evaluation frameworks, and experiment tracking

(Optional) Contribute back to open-source models, tooling, or research