Robotics Engineer, Technical Lead

About Applied Intuition Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co . We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. 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 Nice to have: Experience with state-of-the-art bi-dexterous mobile hardware platforms, including dexterous manipulation and whole body control Familiarity with hardware bring-up, sensor integration, or embedded systems; ability to engage with mechanical and electrical teams at a subsystem level Background in SLAM, 3D perception, or sensor fusion (IMU, lidar, cameras, force/torque) Experience with physics simulators such as MuJoCo, NVIDIA Isaac Sim, or Gazebo Familiarity with ROS/ROS2 or similar robotics middleware Publication record or open-source contributions in robot learning, embodied AI, or manipulation Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the