Robotics Perception Engineer Intern

Gritt Robotics; Sacramento (CA); On-site; USD 33,000 - 60,000; Full time

Job summary

Gritt is seeking a Robotics Perception Engineer Intern to join our team in the SF Bay Area. You will develop perception components on real robot data, build datasets, run experiments, and integrate modules into the live robot stack with demos.

You will work on pose estimation, multi-sensor fusion, and multimodal learning, gaining hands-on experience with state-of-the-art CV and robotics tools. This internship offers mentorship and potential full-time opportunities.

Qualifications

• . Pursuing MS/PhD in CS, EE, Robotics, or related field.
• . Strong Python skills; experience with PyTorch and computer vision fundamentals.
• . Evidence of applied work: projects, competitions, publications, or industry robotics experience.
• . Must be legally authorized to do an internship in the United States for either 3 months or 6 months.

Responsibilities

• Develop and evaluate perception components on real robot data.
• Build datasets and evaluation harnesses; run experiments and report results.
• Integrate your module into the live robot stack and demo it.
• Get hands-on with pose estimation, VLMs, VLAs, 3D scene reconstruction, object detection, and multimodal learning.
• Test your work on real robots at the office.
• Opportunity to publish (for PhD interns).
• Attend Tier-1 industry conferences.
• Example projects could be anything from building a robust 6DOF pose estimation stack that can work in harsh degraded outdoor conditions, to shipping a 3D object detection module for our manipulation stack.

Skills

Python

PyTorch

Computer Vision

Education

MS/PhD in CS, EE or Robotics

Tools

CUDA

Job description

Gritt

is an intelligent system that combines robotics and AI to build the infrastructure that pulls society forward. Gritt deploys via simple attachments to common equipment found on construction sites and autonomously performs labor-intensive tasks, verification, and planning. Gritt systems are already building critical infrastructure in the harshest outdoor environments, starting with large-scale solar. The

founding team

includes experts in robotics and AI from Carnegie Mellon, Stanford, and MIT. Gritt is backed by Obvious Ventures, Union Square Ventures, First Round Capital, Climactic, Congruent Ventures, and other leading firms.

Role: Robotics Perception Engineer Intern

Location: SF Bay Area (in-person)

About Internships at Gritt

Our internships are scoped projects: you own a defined deliverable end-to-end, work with a dedicated mentor, and demo your work to the whole team. Many interns receive return or full-time offers. This will be an internship for one of two durations: 3 months, or 6 months. We offer competitive salaries, and the opportunity to work on a mission with tremendous climate impact.

What you'll get to work on

• Develop and evaluate perception components on real robot data.
• Build datasets and evaluation harnesses; run experiments and report results.
• Integrate your module into the live robot stack and demo it.
• Get hands-on with pose estimation, VLMs, VLAs, 3D scene reconstruction, object detection, and multimodal learning.
• Test your work on real robots at the office.
• Opportunity to publish (for PhD interns).
• Attend Tier-1 industry conferences.

Example projects could be anything from building a robust 6DOF pose estimation stack that can work in harsh degraded outdoor conditions, to shipping a 3D object detection module for our manipulation stack.

What we look for

• Pursuing MS/PhD in CS, EE, Robotics, or related field.
• Strong Python skills; experience with PyTorch and computer vision fundamentals.
• Evidence of applied work: projects, competitions, publications, or industry robotics experience.
• 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.

Nice to have

• Experience with sensor drivers, CUDA, 3D geometry, or multi-sensor fusion.