Seeing Systems
Software Engineering Intern
New
4500 –7500 GBP / monthEuropeTraineesoftware engineeringautonomous systemssensor fusion
Internship role for designing and building core autonomy software stack for drones.
About the company
- Seeing Systems is building autonomous drone systems that can perceive, navigate, and act intelligently in complex real-world environments.
- We focus on advancing autonomy through monocular vision, sensor fusion, and robust system design , enabling drones to operate reliably where traditional systems fail.
- Seeing Systems was founded by brothers Matthew and Alex Le Maitre , combining deep experience across software, robotics, and defense. Matthew is a former Jane Street engineer and top-ranked computer science graduate from the University of Cambridge, with a background in autonomous systems research. Alexander is a self-taught hardware engineer who has been building unmanned systems and military-grade electronics from a young age, including work on explosive ordnance and national security projects.
- We are an early-stage, fast-moving team working at the intersection of robotics, perception, and real-world deployment.
Responsibilities
- We’re hiring a Software Engineering Intern to help design and build the core autonomy stack powering our drones. This is a deeply technical, hands-on role where you’ll work across perception, planning, and systems infrastructure—owning critical pieces of the product from day one.
- You’ll partner directly with the founders to define architecture, make key technical decisions, and ship systems that perform reliably both in simulation and in the field.
- Design and build core components of the autonomous drone stack
- Develop perception and state estimation systems using monocular vision and sensor fusion
- Work with and extend robotics frameworks like ROS / ROS2
- Build and test algorithms in simulation environments such as AirSim , and deploy to real systems
- Implement and optimize SLAM , localization, and navigation pipelines
- Interface with sensors, compute systems, and flight controllers
- Contribute to system architecture across software, hardware, and communications layers
- Rapidly prototype, test in the field, and iterate on real-world performance
- Leverage modern AI tools and workflows to accelerate development and experimentation
- Help define engineering culture, tooling, and hiring as a founding team member
- Within your first 30 days, you'll deploy your first vision-based navigation update to a physical drone and test in the field, and within 90 days, you’ll be co-owner of our internal autonomy stack, responsible for large-scale development and direction of our primary software product.
Requirements
- Strong software engineering skills, with Python preferred (C++, Rust or OCaml is a plus)
- Experience building robotics, real-time, or distributed systems
- Familiarity with ROS / ROS2 and working across simulation + hardware
- Strong intuition for systems, debugging, and performance tradeoffs
- Comfortable operating in ambiguity and moving quickly in a startup environment
- High ownership mindset —you build, test, and ship end-to-end
- Heavy user of AI tools (e.g., claude code) to accelerate output
- Willing to go outside with us and test in the real world!
Nice to have
- Experience with SLAM , visual odometry, or 3D reconstruction
- Background in computer vision (especially monocular/depth estimation)
- Experience with sensor fusion (e.g., IMU + camera, Kalman filters)
- Familiarity with AirSim or similar simulation platforms
- Experience working with drones, UAV systems, or embedded systems
- RF or communications systems experience
- Prior startup or founding engineer experience
Conditions
- Founding-level ownership
- Opportunity to build cutting-edge autonomous systems from first principles
- Work on real-world robotics problems with immediate, tangible impact
- Tight iteration loop between simulation and deployment
- Small, high-agency team moving quickly
- If you’re excited about building autonomous systems that operate in the real world—and want to help define the future of drone intelligence—we’d love to talk.