Experience Fresher-friendly - open to freshers / early-career candidates
About the role
structured by ORIAll open roles AI ### 🤖 AI Intern – Robot Learning - Imitation Learning, Foundation Models, RL (6-12 months) Mountain View, CA (On-Site)/Internship Apply now Share ### About the role Join our AI team to help develop learning and control systems that enable robots to grasp, reorient, and manipulate objects with…
What you will do
- Design, train, and evaluate manipulation policies on real hardware
- Run focused research experiments end-to-end — form a hypothesis, build the ablation, and draw a clear conclusion from noisy real-world results
- Integrate multimodal sensor streams (RGB, depth, proprioception, tactile) into policy architectures
- Contribute to data collection tools and replay infrastructure for learning from human demonstrations
- Work closely with hardware, AI, and perception engineers to close the loop from sensing to control
What they are looking for
- Pursuing a BS or MS in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field.
- Strong foundation in training neural networks — you can take a model from idea to a working, debugged result
- Strong foundation in imitation learning or reinforcement learning
- Experience with vision-based policy learning — diffusion policies, 3D policies, vision-language-action models, video action models
- Strong Python programming skills and experience with PyTorch, JAX, or a comparable machine-learning framework.
- Ability to design careful experiments and work with noisy, real-world robotic data.
- Strong communication skills and enthusiasm for hands-on robotics development.
Nice to have
- Experience with robot simulators (e.g., MuJoCo, Isaac Gym/Lab)
- Familiarity with contact-rich or dexterous manipulation, or tactile sensing
- Experience deploying learned policies to physical systems.
- Publications or preprints at robotics or ML venues (CoRL, RSS, ICRA, NeurIPS, ICML, ICLR)
Before you apply
- A portfolio is recommended where relevant.
- Interview process: two technical interviews and one CEO interview.
- TN sponsorship available for eligible candidates.
Benefits
- Health coverage for interns.
- Lunch and dinner provided.
- Assistance with local transportation costs.
- Fully stocked office kitchen.
- Strong potential for full-time conversion after the internship.
Neural network trainingImitation learningReinforcement learningVision-based policy learningPythonPyTorchJAXRoboticsMuJoCoIsaac Gym/Lab
Full posting text
All open roles
AI
🤖 AI Intern – Robot Learning - Imitation Learning, Foundation Models, RL (6-12 months)
Mountain View, CA (On-Site)/Internship
Apply now Share
About the role
Join our AI team to help develop learning and control systems that enable robots to grasp, reorient, and manipulate objects with human-like dexterity. You will work across simulation, data, and robot experiments to turn cutting-edge manipulation research into robust capabilities on real hardware.
Requirements
- 01Pursuing a BS or MS in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, or a related field.
- 02Strong foundation in training neural networks — you can take a model from idea to a working, debugged result
- 03Strong foundation in imitation learning or reinforcement learning
- 04Experience with vision-based policy learning — diffusion policies, 3D policies, vision-language-action models, video action models
- 05Strong Python programming skills and experience with PyTorch, JAX, or a comparable machine-learning framework.
- 06Ability to design careful experiments and work with noisy, real-world robotic data.
- 07Strong communication skills and enthusiasm for hands-on robotics development.
- 08(+) Experience with robot simulators (e.g., MuJoCo, Isaac Gym/Lab)
- 09(+) Familiarity with contact-rich or dexterous manipulation, or tactile sensing
- 10(+) Experience deploying learned policies to physical systems.
- 11(+) Publications or preprints at robotics or ML venues (CoRL, RSS, ICRA, NeurIPS, ICML, ICLR)
Details & responsibilities
- 01Design, train, and evaluate manipulation policies on real hardware
- 02Run focused research experiments end-to-end — form a hypothesis, build the ablation, and draw a clear conclusion from noisy real-world results
- 03Integrate multimodal sensor streams (RGB, depth, proprioception, tactile) into policy architectures
- 04Contribute to data collection tools and replay infrastructure for learning from human demonstrations
- 05Work closely with hardware, AI, and perception engineers to close the loop from sensing to control
- 06A Proception employee will reach out directly to schedule additional interviews.
- 07A portfolio is recommended where relevant.
- 08Interview process: two technical interviews and one CEO interview.
Compensation & benefits
- 01Health Insurance: Health coverage for interns.
- 02Meals: Lunch and dinner provided.
- 03Commuter Benefit: Assistance with local transportation costs.
- 04Snacks and Drinks: Fully stocked office kitchen.
- 05Immigration Support: TN sponsorship available for eligible candidates.
- 06Career Growth: Strong potential for full-time conversion after the internship.
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