Member of Technical Staff - ML Data

What you'll do

• Design, deploy, and iteratively improve ML methods and workflows for data processing and annotation.
• Build scalable pipelines for real-world and synthetic data, and measure data quality and its impact on model performance.
• Produce and evaluate labels such as captions, camera poses, depth maps, and segmentation masks; collaborate with researchers and engineers.

What they ask for

• 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, including implementation, large-scale application, evaluation, and iterative improvement.
• Strong Python and PyTorch skills, experience training, adapting, and evaluating ML models, and ability to design experiments and analyze errors.

Nice to have

• Publications in computer vision, robotics, or related machine learning fields, with a substantial personal contribution.
• Experience with distributed computing, large-scale inference or data-processing workflows, or distributed data pipelines.

Tools

Python, PyTorch

AI focus

Develop data-focused ML methods and annotation workflows for multimodal foundation world models and Physical AI.