Physical AI Engineer, Autonomous Vehicles 🇺🇸 🇨🇿
About ISEE AI
ISEE AI is an MIT spin-off company building the physical artificial intelligence stack for autonomous industrial vehicle fleets. We are looking for engineers to push the frontier.
ISEE AI is backed by Founders Fund, a top-tier VC fund. One of our customers is Maersk, the world's largest container shipping company. Read more about ISEE on our website or in this TechCrunch article.
A large portion of our core research and engineering team is based in Prague, Czech Republic.
The Role
We are hiring Physical AI Engineers to work at the intersection of machine learning research and real-world robotic deployment.
You'll work across the full ML lifecycle — prototyping models in simulation, validating them against real sensor data, and deploying them onto vehicles operating in live industrial yards. This is not a research-only role: we care about models that work in production, in the rain, under time pressure, on hardware with real-world constraints.
Depending on your background and interests, your work may span computer vision, motion planning, human behavior prediction, or generative simulation.
Role responsibilities
Design, train, and evaluate machine learning models for use in our autonomous driving stack and simulation environment
Contribute to computer vision systems for scene understanding, object detection, and 3D reconstruction
Develop reinforcement learning and imitation learning models for vehicle behavior and motion planning
Build and improve models for predicting the behavior of human-operated vehicles and pedestrians in industrial environments
Build and operate real-world data pipelines, annotation workflows, and evaluation frameworks
Optimize and deploy models for inference on embedded hardware using tools like ONNX and TensorRT
Participate in our weekly ML journal club and contribute to a culture of rigorous, curiosity-driven engineering
Qualifications
- Degree in Computer Science, Machine Learning, Robotics, or a closely related field (Master's minimum, PhD preferred)
- Strong theoretical grounding in machine learning. You understand not just how to use algorithms but why they work
- Hands-on experience with PyTorch and the modern ML toolchain
- Proficiency in Python; C++ experience is a plus for performance-critical components
- Ability to communicate clearly in English, both in writing and in technical discussions
Plus points
- Experience in robotics, autonomous vehicles, or other real-world physical AI applications
- Familiarity with model deployment using ONNX, TensorRT, or similar inference optimization frameworks
- Publication record at top-tier ML, CV, or robotics venues (NeurIPS, CVPR, ICRA, CoRL, etc.)
- 3+ years of industry experience deploying ML systems in production environments
- PhD in Machine Learning, Computer Vision, Robotics, or a related field
What do we offer?
- Meaningful work from day one — you'll be contributing to one of the first commercially deployed autonomous vehicle systems in the world
- Exceptional colleagues — collaborate with engineers and researchers from top academic and industry backgrounds
- Weekly ML journal club — structured time to stay current with research and discuss ideas across the team
- Competitive compensation — reflecting the seniority and impact of the role, generally exceeding market
- Flexible working hours — we care about output, not clock-watching