Powering generalist robotics and world models with multi-million-hour annotated egocentric data, hand tracking, upper-body/whole-body motion capture, tactile sensing, and simulation for OpenAI, Google DeepMind, Meta, Figure, 1X, Skild, Genesis AI, and Dyna... Backed by South Park Commons.
About the role
We are looking for a Robotics Research Engineer / Scientist to develop learning-based methods that enable robots to perform complex tasks in the real world. You will work on robot learning, policy training, and real-world deployment, exploring approaches such as imitation learning, reinforcement learning, and Vision-Language-Action (VLA) models. You will help bridge the gap between research and practical robotic capabilities by developing, training, and evaluating policies on real robotic systems. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A PhD in Robotics, Computer Science, Machine Learning, or a related field, alternatively, substantial hands-on experience developing learning-based robotic systems. Strong MS candidates are welcome
- Strong programming skills in Python and experience with deep learning frameworks such as PyTorch
- Experience with at least one learning-based robotics approach, such as imitation learning, reinforcement learning, diffusion policies, or VLA models
- Understanding of robotic manipulation, perception, control, or visuomotor learning
- Experience designing and conducting experiments to evaluate learned policies
- Strong problem-solving skills and the ability to translate research ideas into working systems
More about this role
We are looking for a Robotics Research Engineer / Scientist to develop learning-based methods that enable robots to perform complex tasks in the real world.
You will work on robot learning, policy training, and real-world deployment, exploring approaches such as imitation learning, reinforcement learning, and Vision-Language-Action (VLA) models. You will help bridge the gap between research and practical robotic capabilities by developing, training, and evaluating policies on real robotic systems.
This role is ideal for someone with strong robotics or machine learning expertise who enjoys hands-on experimentation and pushing the capabilities of learning-based robotic systems.
Develop and train learning-based policies for robotic manipulation and other embodied tasks.
Apply methods such as imitation learning, reinforcement learning, diffusion policies, and VLA models.
Work on visuomotor policies, bimanual manipulation, dexterous manipulation, and generalization across tasks or environments.
Design data collection and training pipelines using robot demonstrations and other relevant datasets.
Deploy trained policies on physical robots and debug performance in real-world...
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