Specialist search for Autonomy hiring

Autonomy engineering covers the software that allows robotic systems to make decisions and navigate the world without constant human input — path planning, localisation, mapping, behaviour trees, prediction, and the full decision-making stack. It sits between perception (what the robot sees) and controls (how the robot moves), and it is where the hardest algorithmic problems in deployed robotics live.

The work spans classical and learned approaches. Some teams build entirely on probabilistic methods and SLAM variants; others are integrating learned behaviours alongside classical planners. The best autonomy engineers understand both, and know when each approach is appropriate in a production system operating under real-world constraints.

The candidate pool for production autonomy work is one of the narrowest in all of robotics. There is a significant difference between engineers who have worked on deployed systems — systems that need to handle edge cases, degraded sensor conditions, and real-world failure modes — and those who have only worked in research or simulation. Most hiring managers can articulate this distinction clearly. Finding engineers who meet it is much harder.

Competition is intense. Well-funded self-driving, humanoid, and AMR programs are all competing for the same shallow pool of engineers with production autonomy experience. Engineers who have shipped autonomous systems into real customer environments are not actively looking, and they are not reachable through standard channels.