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DeepReach is seeking a Robotics Research Intern to contribute across VLA, robot learning, and computer vision for robotics. This role emphasizes applying research to real systems, training or fine-tuning visuomotor models, and building data curation tools for production robotics.
You will read papers, implement ideas quickly, and iterate independently within a fast-moving startup. Strong coding in Python and PyTorch experience are desired.
DeepReach is building the next-generation data infrastructure for robotics. We help bridge the gap between promising robot models and real-world deployment by building the systems, data pipelines, and learning loops needed to make robots improve in production.
We believe robotics progress will be driven not just by better models, but by better data engines: how data is collected, filtered, evaluated, and turned into measurable gains on real tasks. Our team works across robot deployment, teleoperation, data generation, model training, and evaluation, with a strong bias toward hands-on execution and fast iteration.
As a Robotics Research Intern, you will work on applied problems across VLA, robot learning, and computer vision for robotics. This is a generalist role for candidates who are excited about embodied AI and want to contribute to real systems rather than only benchmark results.
You may work on projects such as training or fine-tuning visuomotor models, improving perception pipelines, building data curation tools, reproducing recent research, or helping connect model improvements to real deployment tasks. We are looking for people who can read papers, implement ideas quickly, and iterate independently in a fast-moving startup environment.
Real-world robotics experience is a plus, but strong project or research experience is also acceptable.
Remote (U.S. only)
3–6 months