Robotics Engineer, Technical Lead

About the role

This is a founding technical role helping build and shape Applied Intuition's robotics organization from the ground up. You will set the technical direction for robotics software and AI, write production code, and build functional demos on physical hardware from day one. The role is weighted heavily toward software and learned behaviors, with the expectation that you can engage meaningfully across the hardware stack when needed. At Applied Intuition, you will: Define and own the technical architecture for humanoid robotics software, spanning perception, planning, control, and learned behaviors Write production-quality code in Python and C++ and ship it to physical robots - this is a hands-on individual contributor role first Design, train, evaluate, and deploy learning-based policies for manipulation and locomotion Build functional demonstrations on multiple robot hardware platforms that prove out capabilities and inform the product roadmap Establish simulation infrastructure and validate behaviors in physics-based environments before deploying to hardware Instrument robots, analyze telemetry and failure data, and iterate quickly to improve robustness in real-world conditions Work with teleoperation and data collection pipelines to generate training data and close the sim-to-real gap Identify and recruit the next engineers on the team We're looking for someone who has: BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, or a related field, or equivalent hands-on experience 7+ years of experience in robotics software development, with a meaningful portion on physical humanoid, legged, or highly dexterous manipulation platforms Proven track record shipping learning-based systems - behavior cloning, RL, or VLA policies - to real robots in production or near-production settings Strong proficiency in Python and C++ for robotics and ML systems; experience with PyTorch or equivalent deep learning frameworks Deep understanding of robotics fundamentals: kinematics, dynamics, control theory, state estimation, and perception Experience building and evaluating visuomotor or multimodal policies end to end, from data collection through deployment Ability to operate independently in an early-stage environment, make architectural decisions with limited information, and build from scratch Comfort on the lab floor - debugging physical robots, running hardware-in-the-loop tests, and iterating on live systems