Software Engineering Intern
Software Engineering Intern at Seeing Systems — London, England, GB
- Company: Seeing Systems
- Location: London, England, GB
- Employment type: INTERN
- Salary: USD 4500–7500 / year
- Posted: 2026-07-17
About this role
About Us
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.
The Role
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.
What You'll Do
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.
What We're Looking For
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
Why Join
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.