Team Lead

Join SE3 Labs as Team Lead - Visual Localization

Build and lead the team that makes our autonomous systems know where they are.

About SE3

SE3 Labs builds spatial intelligence and autonomy software for unmanned systems. We combine 3D computer vision, state estimation and AI to help autonomous platforms perceive their surroundings, know where they are and operate when GPS and other sensors become unreliable. Defence is a core application of our work today.

We are growing to a team of 100+ people. Join at a stage where you can shape our localization technology, help build the team and grow your responsibilities as the company expands.

Our founding team’s research has received more than 90,000 citations. You will work closely with technical founders and engineers with deep experience in computer vision and autonomous systems, turning that research depth into systems that work in the field.

About the Role

You will hire and develop engineers, own the localization roadmap, set priorities and deliver a system that works on real sensors, within onboard compute limits and in difficult field conditions.

You will remain closely involved in architecture, core algorithms and debugging, with roughly 20–40% of your time spent coding. Work with senior individual contributors to set technical direction and with robotics software, embedded, hardware and field teams to turn it into a reliable deployed system.

What You’ll Work On

• Build the Team: Hire excellent localization engineers, assess their technical work and help them develop. Give clear feedback, establish ownership and build a team that can solve difficult problems together.

• Roadmap and Delivery: Own the roadmap and delivery of VIO, SLAM, sensor fusion, calibration, mapping and relocalization. Turn mission requirements and observed failures into specific engineering priorities.

• Technical Direction: Guide architecture and core algorithm decisions with the team. Make the tradeoffs between accuracy, robustness, latency, memory and power explicit and test them against real data.

• Evaluation and Replay: Build the evaluation and replay loop so the team can make most improvements from recorded data. Set measurable criteria for accuracy, robustness and runtime, and maintain regression tests that catch failures before deployment.

• Hands-On Engineering: Stay involved in critical algorithms, production code and difficult debugging. Help resolve failures caused by timing, calibration, vibration, motion blur, poor lighting and degraded sensors.