We are hiring Machine Learning Engineers who have shipped models into production systems, not just papers. If you obsess over data quality, evaluation rigor, and the brutal gap between offline metrics and real-world behavior, you will be at home here.
You will work across data curation, model architecture, training infrastructure, and on-device inference. The problems span perception, manipulation, control, and the operations layer that keeps everything improving over time. You will partner closely with robotics and software engineers to put your work into customers' hands.
Deep familiarity with modern ML frameworks is expected. Experience with embodied learning, sim-to-real, or efficient inference on edge hardware is a strong plus. We care less about which models you have used and more about how you reason about what to build next.
If you have ever shipped a model that quietly made a product better, tell us that story.