Software Engineer - Robotics / Autonomy -> Stealth Physical AI Startup

Software Engineer - Robotics / Autonomy -> Stealth Physical AI Startup

A world-class early-stage team, founded by former executives and founding members from Palantir and Anduril is applying the tools and thinking of autonomous systems to one of the most consequential problems in the physical world. Backed by an elite VC and built by top engineers from Google, Zipline, and the best autonomy programs in the country, this team is bringing closed-loop AI control to the world's industrial infrastructure for the first time.

The company connects directly to the control systems of complex industrial facilities (manufacturing, chemicals, biologics, oil & gas) ingesting sensor data, building real-time models of physical reality, and autonomously adjusting production processes to drive output and yield. This is not a robotics company in the traditional sense i.e. they don't build hardware, but the engineering challenges are identical: perception, sensor fusion, closed-loop control, and real-world actuation under uncertainty. This engineer will work directly on customer problems, apply both classical control methods and state-of-the-art ML approaches, and contribute to a growing platform of reusable autonomy components. Paid pilots are live, revenue is imminent, and the team is small enough that every hire shapes the technical direction of the company.

The industrial automation market sits at $227B today and is heading toward $500B, and virtually none of it has a real intelligence layer. The autonomy engineers who join now will be among the first to bring the discipline and rigour of modern AI-driven control to an industry that has been waiting for it.

Key experience:

• 3 Years' experience in Software Engineering with a focus on Robotics / Autonomous Systems
• Background in autonomous systems - autonomous vehicles, defense autonomy, aerospace GNC, or industrial robotics, with a track record of shipping software that controls or actuates real-world physical systems
• Strong foundations in perception, sensor fusion, or SLAM, experience taking noisy, real-world sensor data and producing reliable models of physical state
• Proficiency in C and/or Python; familiarity with ROS/ROS2, simulation environments (Gazebo, Isaac, or similar), and classical control theory
• Background in physics, mechatronics, or a related engineering discipline is strongly preferred; experience bridging classical and ML-based control approaches is a significant plus

This is a rare chance to join a founding team applying the most advanced thinking in autonomy to an industry that has never had it - building systems that directly increase the output of the world's physical production infrastructure, alongside some of the best engineers in the field.