Boost Robotics combines digital infrastructure with physical agents to revolutionize robotics solutions. Backed by Y Combinator.
About the role
We’re not hiring for a checklist - we’re hiring for exceptional people. If you move fast, think deeply, and love building things that actually work, you’ll fit right in. We’re friends and builders who hold the highest standards for ourselves and our work. Joining us means having a say in everything - the culture, the rituals, the engineering stack, and what our robots look like. You won’t just work here - you’ll help create what “here” means.
What they're looking for
- Background in Robotics, Computer Science, Machine Learning, or a related field (MS/PhD preferred)
- Experience training large manipulation models (diffusion policies , VLAs)
- Experience developing and deploying learning-based control and perception algorithms on real robots
- Experience with common ML tools, architectures, and workflows
- Strong foundation in classical manipulation, control theory, and motion planning
- Comfort working in small, fast-paced teams where experimentation is constant and results matter
More about this role
Boost Robotics is developing the next generation of autonomous systems that monitor and maintain the world’s digital infrastructure. Backed by Y Combinator , our team consists of former CMU Robotics and Boston Dynamics engineers who have worked on robot systems in defense, agriculture, logistics, and industrial inspection.
The mission? Bring dependable, intelligent robotics to some of the most important and fastest-growing infrastructures powering the world’s digital backbone - data centers.
- Deploy modern behavior cloning and reinforcement learning policies for dextrous tasks in the data center, with a focus on high success rates.
- Lead the software infrastructure for data collection, training, and real-time operation.
- Stay at the frontier of robotics learning research and translate it into production-ready systems that push the boundaries of today’s state of the art.
- Background in Robotics, Computer Science, Machine Learning, or a related field (MS/PhD preferred).
- Experience training large manipulation models (diffusion policies , VLAs)
- Experience developing and deploying learning-based control and perception algorithms on real robots.
- Experience with common ML...
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