ML Engineer Internship

At COCO Robotics, we are redefining the future of last-mile delivery through the power of Physical AI. Our fleet of autonomous delivery robots blends advanced robot learning, cutting-edge machine learning, and AI-driven perception and planning to create real-world impact in communities every day. By joining us, you’ll contribute to building intelligent robotic systems that don’t just operate in simulation, but transform the way goods move in the real world.

As an Engineering Intern, you will be immersed in projects at the intersection of robotics, AI, and real-world deployment. From improving the perception systems that allow our robots to safely navigate city sidewalks, to developing learning-based algorithms that make them more adaptive and efficient, you’ll see how AI research translates into tangible impact at scale. This is a rare chance to work on systems that are already out in the wild, delivering real value to businesses and customers.

You’ll also be mentored by world-class AI and robotics experts, gaining hands-on experience in a dynamic startup environment where curiosity, creativity, and technical rigor drive innovation. Whether you’re passionate about robot learning, computer vision, motion planning, or large-scale ML systems, you’ll have the opportunity to learn, experiment, and contribute directly to the future of autonomous delivery.

Please note this internship opportunity is mainly for undergrad/MS students already living in LA area. If everything goes well, the internship could be turned into a full-time engineer job.

Scope of Work:

1. Preparing video data and meta-data for ML model training

2. Training, fine-tuning, and improving ML models

3. Testing and deploying the trained ML models on the real COCO robot

Required/Preferred Competencies:

1. (Required) Solid experience in deep learning and computer vision (3D vision, cameras, object detection, image classification, etc)

2. (Required) Proficiency in PyTorch, C++, and GPU training, and knowledge in ROS system

3. (Preferred) Experience in mobile robots, autonomous driving, embodied robotic system like Nvidia Jetson

4. (Preferred) Experience in programming competitions, hackathon, and code contributions to open-source projects

5. (Preferred) Experience in simulation and reinforcement learning

Time commitments and compensation:

1. Minimum six months if part-time (two-day-per-week below) or three months if full-time

2. Minimum two-day-per-week commitment

   • Live in LA area

   • Able to come to the HQ office in-person at least ONE DAY per week (near Venice beach)

   • Find time to work between the school days for another 8 hours

3. Compensation: $300 - $400 per day if part-time, or further determined if full-time