Senior Perception Engineer

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.

What you'll do

We are seeking a Perception Engineer to develop the systems that enable our autonomous machines to understand and interact with the physical world.

You will work on perception problems at the intersection of computer vision, machine learning, robotics, and autonomous systems, building models and systems that transform real-world sensor data into reliable representations of the environment.

Depending on your background and area of expertise, you may:

• Design, train, and deploy machine learning models for perception in autonomous systems. • Develop algorithms for object detection, classification, segmentation, tracking, and scene understanding. • Build systems for 3D perception and geometric reasoning using cameras, LiDAR, radar, or other sensors. • Develop approaches for multi-sensor and multi-modal fusion, combining complementary sensor information into robust representations of the environment. • Build temporal models that reason about objects, motion, trajectories, and changes in the environment over time. • Improve perception performance across challenging real-world conditions, including occlusion, sensor noise, changing environments, and edge cases. • Develop data, training, evaluation, and experimentation pipelines that accelerate perception development. • Define metrics and evaluation methodologies that connect offline model performance to real-world system behavior. • Optimize perception models and systems for deployment on resource-constrained or latency-sensitive robotic platforms. • Investigate failures observed in deployed systems and translate those findings into improvements across models, data, and architecture. • Collaborate closely with AI Research, Robotics, ML Infrastructure, Software, Hardware, and Systems Engineering teams.