To build robust, high-quality datasets that fuel modern perception, SLAM, and manipulation models for Fortune 500 companies and government institutions
Requirements
- 3–5 years of hands-on experience in robotics, applied ML, or computer vision
- Strong understanding of robotics concepts such as perception pipelines, SLAM, or sensor fusion
- Familiarity with basic ML training and evaluation, particularly for computer vision or multi-modal data tasks
- Ability to read and synthesize ML research papers relevant to robotics
- Experience with tools such as ROS, CVAT, Roboflow, or custom labeling platforms
- Some exposure to model fine-tuning (e.g., with PyTorch, TensorFlow, or Hugging Face)
Responsibilities
- Help define and evolve labeling schemas for robotic perception tasks
- Contribute to small-scale model fine-tuning
- Translate model needs into precise data specifications
- Perform basic experiments to assess data effectiveness and model improvement
- Collaborate with ML, robotics, and data labeling teams to turn model and benchmark requirements into clear, actionable data specs
- Write clear documentation and present technical updates to collaborators and stakeholders
- Contribute to quality control processes—build checklists, gold sets, and feedback loops that ensure consistent, scalable labeling outcomes
Other
- Excellent written and verbal communication skills—comfortable translating technical needs across disciplines
- Strong collaboration skills and a collaborative mindset
- Ability to work at Start-Up Speed and adapt to changing priorities
- Comfortable with flexible working hours and full-time remote opportunity
