Member of Technical Staff - ML Data

Highlights

• Build next-gen multimodal foundation world models for Physical AI.
• Design ML methods for data selection, enrichment, and quality assessment.
• Build reliable workflows for large-scale real-world and synthetic data.

Ideal candidate

Research-minded ML builder who loves owning data problems end-to-end, from method design to deployment. You care about rigorous experimentation, data quality, and pushing Physical AI forward in a fast-moving team.

Requirements

• Master's or Ph.D. in Computer Science, Engineering, or a related technical field, or equivalent hands-on experience.
• Demonstrated ability to develop original ML methods, evidenced by peer-reviewed publications or substantial research contributions with rigorous experimental validation.
• Experience owning the full lifecycle of an ML method: designing and implementing the approach, applying it to large-scale data, evaluating results, and improving it through successive iterations.
• Strong Python and PyTorch skills, with experience training, adapting, and evaluating machine learning models.
• Ability to design controlled experiments, establish meaningful metrics, and analyze errors to guide improvements.
• Strong software engineering skills, with an emphasis on reproducibility, reliability, and maintainable code.