AI Research Intern; BS​/MS

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 AI, hardware, software, 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 researchers, roboticists, engineers, 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.

We are seeking an AI 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 Perception, World Models and Action 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.

• Integrate and adapt emerging AI research into internal model pipelines, validating performance on real-world datasets and simulation.
• Prototype and evaluate RL, trajectory planning, and distillation algorithms based on state-of-the-art literature.
• Train and fine-tune multimodal models that map real-time sensor inputs and behavioral goals to vehicle actuation.
• Experiment with world model architectures using multi-sensor log data to improve simulation fidelity and trajectory querying.
• Analyze edge cases and failure modes in novel driving environments to iterate on model performance and stability.
• Run rigorous simulation experiments alongside research and validation teams to identify performance bottlenecks and track model improvements.

• Education: Currently enrolled in a Bachelor's or Master's degree program in Computer Science, EECS, Robotics, AI, or a closely related field.
• Core Expertise: Coursework, project experience, or research background focused on at least one of the following domains:
• Vision-Language-Action (VLA) models or embodied AI
• Reinforcement Learning (RL), trajectory optimization, or decision-making systems
• Large-scale multimodal Transformer architectures applied to robotics or spatio-temporal data
• Framework Fluency: Advanced hands-on proficiency with PyTorch or JAX for training and fine-tuning large-scale neural networks.
• Programming: Proficiency in Python and working knowledge of C++.

• Prior research, project, or internship experience in autonomous driving, mobile robotics, or spatial AI.

At Atoms, you’ll work on one of the defining challenges of our time bringing automation into the physical world to drive real, lasting impact. We exist to uncover valuable unknown truths and turn them into progress, which means constantly pushing beyond what’s known and building what doesn’t yet exist. The work is ambitious and often challenging, but it’s grounded in a shared sense of purpose and a team…