about 3 hours ago
Responsibilities
- Design and implement tooling for efficient annotation and curation of robot experience data.
- Profile, quantize, and distill ML models to reduce inference latency and memory footprint.
- Build evaluation harnesses to benchmark optimized model performance against baseline.
- Connect annotation outputs and optimized model artifacts with existing artifact storage and training pipelines.
- Produce design docs, runbooks, and example configurations for post-internship adoption.
Requirements
- Proficiency in Python for writing clean, tested, maintainable code.
- Comfortable working in a Linux environment with tools like Git and Docker.
- Hands-on experience with ML frameworks such as PyTorch.
- Coursework or project experience in robotics, including kinematics and control.
- Experience with data pipelines for moving data between annotation, training, and evaluation stages.
- Preferred experience with data annotation workflows and labeling interfaces.