Staff Machine Learning Engineer - Perception

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

As a Senior Staff Machine Learning Engineer focused on Perception, you will be one of the foundational technical leaders of Atoms' AI organization. You will help define how our machines transform raw sensor data into rich representations of the physical world. You'll work across camera, LiDAR, radar, audio, and other sensor modalities to build perception systems capable of operating in complex, dynamic real-world environments.

This is not simply a role focused on improving an existing perception stack. You will have the opportunity to help determine what that stack should become. You will work closely with AI research, robotics, autonomy, and engineering leaders to develop perception architectures that connect traditional perception capabilities with emerging approaches in world models and foundation models for physical AI.

This is a deeply technical individual contributor role with significant influence over Atoms' technical direction.