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About the Role
Develop software and machine learning for dexterous manipulation, turning research ideas into robot capabilities through experiments, model development, integration, and testing on physical hardware. This hands-on role requires collaboration with robotics, software, and hardware engineers to ensure reliable manipulation behaviors.
Responsibilities
- Develop and evaluate software and machine learning approaches for dexterous robotic manipulation.
- Build data collection and evaluation workflows to measure manipulation performance and understand failures.
- Implement research ideas, run experiments, and compare approaches.
- Integrate learned models and manipulation behaviors into robot software.
- Test on physical robots, debug failures, and improve reliability.
- Document results and collaborate with software and hardware engineers to turn research into working capabilities.
Requirements
- Strong programming skills and a foundation in robotics and machine learning.
- Experience implementing and evaluating models or robotics algorithms.
- Ability to design experiments and reason clearly about results.
- Comfort debugging software on physical robots.
- Clear communication and ownership from experiment through implementation.
Skills
- Robotic manipulation
- Robot learning
- Imitation learning
- Reinforcement learning
- Robot datasets
- Simulation
- Perception
- Control
Location
- San Francisco
Work Type
- Onsite
- Full-time
About the Company
- We believe planet earth can thrive and be alive. Robots should manufacture goods, clean roadways, tidy our rooms, build more homes, cook healthy food, and lower the cost of living. We aren’t quite there yet, robots are too expensive, too difficult to program, fragile, and unfriendly. Bracket Bot is changing that.
Equal Opportunity
- Bracket Bot is an equal opportunity employer. We’re building a diverse team and welcome applicants from all backgrounds.