Robotics ML Engineer Intern - Real-World Robot Learning

Gritt; South San Francisco (CA); On-site; USD 39,000 - 58,000; Part time

Benefits offered by this job

Mentorship program

Potential full-time offer

Hands-on robotics experience

Job summary

Gritt in SF Bay Area is seeking a Robot Learning Engineer Intern to work on real-world robotics tasks integrating ML, RL, and perception. This in-person internship offers end-to-end ownership of a defined deliverable, mentorship, and opportunities to present to the team.

You'll train policies for real robot tasks, build data pipelines, deploy on hardware, and test in the office. Ideal candidates are pursuing MS/PhD in ML/Robotics/CS, proficient in PyTorch, and able to work independently with

Qualifications

• Pursuing MS/PhD in ML, Robotics, CS, or related field.
• Strong PyTorch; solid grounding in deep learning and IL/RL.
• Applied evidence: publications, open-source, or substantial course/competition projects.
• Should be comfortable taking ownership of tasks with light supervision.
• Must have excellent problem-solving skills.
• Legally authorized to do an internship in the United States for either 3 months or 6 months.

Responsibilities

• Train policies (imitation learning, RL, or fine-tuned foundation models) for real robot tasks.
• Build data collection and evaluation pipelines; run ablations.
• Deploy policies on hardware and iterate against real-world performance.
• Test your work on real robots at the office.
• Get hands-on with pose estimation, VLM, VLA, 3D scene reconstruction, object detection, and multimodal learning.
• Get the opportunity to publish (for PhD interns).
• Attend Tier-1 industry conferences.

Job description

Gritt in SF Bay Area is seeking a Robot Learning Engineer Intern to work on real-world robotics tasks integrating ML, RL, and perception. This in-person internship offers end-to-end ownership of a defined deliverable, mentorship, and opportunities to present to the team.

You'll train policies for real robot tasks, build data pipelines, deploy on hardware, and test in the office. Ideal candidates are pursuing MS/PhD in ML/Robotics/CS, proficient in PyTorch, and able to work independently with