Robot Learning Engineer Intern

About the role

The Robot Learning Engineer Intern will work on training policies for real robot tasks using methods such as imitation learning, reinforcement learning, and fine-tuned foundation models. They will also build data collection and evaluation pipelines, deploy policies on hardware, and iterate based on real-world performance.

Responsibilities

• Train policies for real robot tasks using methods like imitation learning, reinforcement learning, and fine-tuned foundation models.
• Build data collection and evaluation pipelines.
• Deploy policies on hardware and iterate based on real-world performance.
• Test policies on real robots at the office.
• Get hands-on with pose estimation, VLM, VLA, 3D scene reconstruction, object detection, and multimodal learning.
• Opportunity to publish (for PhD interns).
• Attend Tier-1 industry conferences.

Requirements

• Pursuing MS/PhD in ML, Robotics, CS, or related field (exceptional undergraduates welcome).
• Strong PyTorch; solid grounding in deep learning and one of IL/RL.
• Applied evidence: publications, open-source, or substantial course/competition projects.
• Comfortable taking ownership of tasks with light supervision.
• Excellent problem-solving skills.

Qualifications

• Likely to be pursuing MS/PhD in ML, Robotics, CS, or related field.
• Exceptional undergraduate candidates may also be considered.

Skills

• Python programming.
• Experience with PyTorch.
• Deep learning knowledge, including imitation learning, reinforcement learning, and fine-tuned foundation models.
• Experience with simulators (Isaac, MuJoCo).
• Experience with VLA/foundation models.
• Experience with tele-op data collection.
• Experience with real-hardware deployment.

Benefits

• Competitive salary.
• Opportunity to work on a mission with tremendous climate impact.
• Internship opportunities for return or full-time offers.

Pay

Competitive salary.

Schedule

Full-time, On-site.