Robotics Software Engineering Intern

Gritt Robotics Inc•Belmont, CA

About The Position

We’re looking for a software engineering intern, experienced in robotics applications, to join our team. As an intern, you will play a pivotal role in building the software that powers our robots and enables our on-field operations. You will work on challenging problems around perception, manipulation and navigation in outdoor environments. You'll need to thrive in a fast-paced, dynamic startup environment where you'll wear multiple hats and have a direct impact on our product's evolution. Ideally, you have a proven track record of writing software for robotic applications, and you're passionate about pushing the boundaries of what's possible in robotics with AI. 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.

Requirements

B.S/M.S degree in robotics, vision, computer science, mechanical engineering, electrical engineering or other engineering disciplines (or equivalent experience).
2+ years of hands-on experience developing AI-driven solutions for robotics applications.
Experience in ROS2, database management systems, GPU programming, front-end and back-end programming.
Experience with building software that was deployed on robots operating in physical world.
Extensive experience with Python and common frameworks like PyTorch.
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

Develop and deploy production-grade AI software for robotic applications in outdoor construction.
Scale and improve our existing software stack to manage fleet of robots
Build dashboards for performance metric tracking and model improvements.
Work across the stack on planning, perception, control, and learning.
Develop and improve data pipelines, training and validation infrastructure.
Optimize training and inference times/memory footprint on GPUs.