ML/AI Research Internship - PhD

About this role

Who we are

Atoms is building the machines that power the next era of progress.

Over the last decade, software has transformed the digital world. But the physical world, where food is made, minerals are mined, goods are moved, and industries are run, remains far less intelligent, far less efficient, and far more constrained. We’re changing that.

Atoms builds Physical AI real-world robots for the industries that move civilization forward, starting with food, mining, and transport. Our systems are designed to understand, predict, and control the real world with precision, turning complex physical operations into something more reliable, more scalable, and more productive.

This work requires more than robotics. It requires deep integration across hardware, software, AI, operations, manufacturing, and real estate. We don’t just build machines in a lab. We deploy them into real environments, operate them, learn from them, and improve them until they work at scale.

We are roboticists, engineers, operators, and builders. We believe the next great technology companies will not only transform information, but the physical systems that shape everyday life.

If you want to work on hard problems with real-world impact, join us.

About the Role

We are seeking a visionary AI/ML Research Intern to join our founding team and bridge the gap between high-level AI research and real-world physical actuation for our next-generation autonomous transport platforms.

In this role, you will contribute to core research initiatives on World Models and Vision-Language-Action (VLA) models. You will help translate cutting-edge theoretical breakthroughs into scalable, real-world deployment on physical autonomous systems, driving how our platforms perceive, simulate, and navigate complex environments.

What you'll do

• Research and develop cutting-edge RL and distillation techniques for trajectory planning.

• Integrate emerging research from the broader AI community, identifying and prototyping the most promising solutions.

• Design and prototype end-to-end multimodal models that translate real-time visual perception and high-level behavioral goals into physical vehicle actuation.