AI Engineer; SLAM

About Us

Foundation is developing the future of general purpose robotics with the goal to address the labor shortage. Our mission is to create advanced robots that can operate in complex environments, reducing human risk in conflict zones and enhancing efficiency in labor‑intensive industries. We are on the lookout for extraordinary engineers and scientists to join our team. Your previous experience in robotics isn’t a prerequisite — it’s your talent and determination that truly count.

We expect that many of our team members will bring diverse perspectives from various industries and fields. We are looking for individuals with a proven record of exceptional ability and a history of creating things that work.

We like to be frank and honest about who we are, so that people can decide for themselves if this is a culture they resonate with. Please read more about our culture here (Use the "Apply for this Job" box below)..

• You are highly technical - regardless of the role you are in. We are building technology; you need to understand technology well.
• You care about aesthetics and design inside out. If it’s not the best product ever, it bothers you, and you need to “fix” it.
• You don’t need someone to motivate you; you get things done.

• A humanoid operating in unstructured, real‑world environments must know exactly where it is and what surrounds it at all times — SLAM is the foundational system that makes that possible.
• Our humanoid needs to build and maintain accurate, real‑time maps of dynamic environments while simultaneously localizing itself with centimeter‑level precision — a problem that requires a dedicated, senior‑level focus.
• Off‑the‑shelf SLAM solutions are not sufficient for a full‑body humanoid operating across floors, stairs, cluttered rooms, and outdoor terrain — we need custom, embodied solutions built from the ground up.
• As we move from controlled lab settings to real‑world deployment, robust localization and mapping becomes a hard dependency for every upstream system — perception, planning, and manipulation all rely on it.
• We are scaling our autonomy stack and SLAM is the critical infrastructure layer that must be production‑ready before the rest of the system can follow.
• This role directly impacts how our humanoid understands its place in the physical world — it is foundational, not peripheral.

• Deep knowledge in vision for robotic systems.
• Hands‑on experience implementing SLAM pipelines in C++ and Python — you have built and tuned these systems end‑to‑end, not just integrated existing libraries.
• Strong working knowledge of modern SLAM frameworks: ORB-SLAM3, RTAB-Map, Cartographer, LIO-SAM, or KISS-ICP — and the ability to extend or rewrite core components when needed.
• Experience with neural or learned SLAM approaches (DROID-SLAM, iMAP, NeRF-SLAM).
• Experience with legged or humanoid‑specific odometry challenges.
• Bonus: experience with multi‑session and multi‑agent mapping.
• Comfortable with probabilistic state estimation, Kalman filtering (EKF/UKF), and particle filters as they apply to real‑time localization under uncertainty.
• Familiar with loop closure detection methods, place recognition networks and strategies for long‑term map consistency in changing environments.
• Hands‑on experience with simulation environments such as Isaac Lab, Mu Jo Co  for development, testing, and sim‑to‑real validation.