Backed by Initial Capital.
About the role
As an ML Intern on our team, you will help bridge the gap between high-level AI research and real-world physical actuation for our next-generation autonomous transport platforms. Working alongside senior engineers, you will contribute directly to production-grade models, real-time edge pipelines, and multi-sensor data systems that power our physical machines. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Currently pursuing a BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Data Science, or a related technical field
- Strong foundation in deep learning concepts and experience with modern frameworks like PyTorch or JAX (through coursework, research, or prior internships)
- Hands-on programming experience in Python, familiarity with C++ is a plus
- Academic coursework, project experience, or research in one or more relevant domains: Computer Vision, Spatial-Temporal Modeling, Reinforcement Learning, Model Optimization, Model Evaluation, or Data Engineering
- Familiarity with robotics data structures or multi-sensor processing (Cameras, LiDAR, or Radar) is highly preferred
- A passion for solving complex, messy real-world engineering problems and deploying AI into physical systems
More about this role
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...
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