AI Engineer

Description Mentee Robotics, now part of Mobileye, brings world-class robotics expertise, together with Mobileye's decades of leadership in computer vision, machine learning, and autonomous driving technologies. Building on that foundation, Mentee by Mobileye is creating the "MenteeBot", the AI-first humanoid robot that combines perception, reasoning, learning, and advanced dexterous manipulation, designed to work alongside people in their everyday lives, at the workplace and in the home. At Mobileye, our technologies power more than 230 million vehicles worldwide and have helped shape the future of autonomous mobility. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for real life.

Responsibilities

LLM- and VLM-based agents that plan tasks, call robot skills as tools, verify outcomes and recover from failure, along with the harnesses that evaluate them in simulation and on the robot. You will develop advanced data-generation methods for deep learning models, combining 3D simulation, reinforcement learning and spatial agents to produce realistic, diverse training data at scale. You will reconstruct real environments and objects with Gaussian splatting and 3D computer vision, and bring them into simulation with correct geometry, so our models train where they will be deployed. You will take this work from prototype to production-grade pipelines on distributed GPU compute.

Requirements

B.Sc. in Computer Science, Engineering, or a related field. 4+ years of hands-on experience in machine learning, computer vision, or robotics software engineering. Python Expertise: Extensive experience and strong proficiency in Python, a must-have. Deep learning: Proven experience building and scaling deep learning pipelines (PyTorch), beyond just using existing ones. Breadth: Hands-on experience in at least one of agentic LLM/VLM systems, simulation/RL data generation, or 3D reconstruction, and familiarity with the others.

Advantages M.Sc. or Ph.D. in Computer Science, Robotics, Computer Vision, or a related field. Experience with robotics simulators (e.g. Isaac Sim / Isaac Lab, MuJoCo), reinforcement learning, or sim-to-real transfer. Experience with Gaussian splatting / NeRF, SfM/SLAM (e.g. COLMAP), or meshes for simulation. Experience applying foundation models to robotics: VLM planners or verifiers, VLA models, open-vocabulary perception. Comfortable working in cloud and distributed environments (e.g. AWS, SLURM) and with ROS 2 on real robotic platforms.