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Software Engineering Intern

Spaice TechLondon🇬🇧United KingdomPosted 14 Sept 2026

Why This Role Stands Out

This internship offers a unique opportunity to develop critical infrastructure and deployment tools for cutting-edge autonomous vehicle technology, allowing you to see your code directly impact real-world missions. You'll thrive here if you're eager to gain hands-on experience building robust systems alongside a mission-driven team, and you're encouraged to apply to contribute to groundbreaking advancements in aerospace and defense.

Quick Overview

Seniority
Entry Level
Employment type
Full Time
Location
London, United Kingdom
Posted
14 hours ago
RoboticsC++GitPython

Job Description

About SPAICE

SPAICE is building the geospatial intelligence layer for autonomous vehicles operating where GNSS is unavailable, unreliable, or denied. Our Spatial AI enables drones and satellites to determine their position, understand their surroundings, and transform every detection into actionable, geo-referenced intelligence. From denied airspace on Earth to complex orbital environments, SPAICE delivers resilient navigation and persistent situational awareness in any condition.

At SPAICE, you’ll work on some of the hardest autonomy challenges across air and space, developing technology for GNSS-independent flight, orbital awareness, formation flying, and autonomous operations. You’ll work alongside a mission-driven team and leading aerospace and defence partners, turning advanced research into systems with a tangible impact on real-world missions.

About the Role

In this internship, you'll build the systems that get software onto aircraft, not code that sits on a shelf. As a Software Engineering Intern, you'll join the Infrastructure & Product team to build the build tooling, test harnesses, data pipelines, and internal tools that let a small team ship autonomy software to real missions. Deployment tooling that puts a new build on a flight computer in one command. Test harnesses that catch a navigation regression before it ever reaches an aircraft. Pipelines that turn a field trial's raw flight logs into answers in minutes, not days. These are the challenges you'll help solve.

Expect to write code that gets reviewed, merged, and used by the team. Expect to see the hardware your work runs on. Expect to leave with something real you can point at.

What You’ll Work On

  • Build deployment and release tooling for embedded flight computers and edge-AI hardware, covering cross-compilation, containerisation, configuration management, and over-the-air updates.

  • Help build the test and evaluation infrastructure behind SPAICE's Spatial AI, replaying recorded flight data to catch navigation regressions before they reach an aircraft.

  • Develop data pipelines that ingest logs and sensor recordings from field trials, handling volume and sensor time alignment to make every flight searchable, replayable, and comparable.

  • Build the internal tools and product surfaces. Work on the visualisations, dashboards, CLIs, configuration tooling through which engineers and customers inspect and operate the system.

  • Collaborate with SPAICE's autonomy and perception engineers and cross-disciplinary teams, delivering well-tested, high-performance code into HIL/SIL setups and real missions.

What We’re Looking For

  • Bachelor's or Master's student, or a recent graduate, in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or a related technical field.

  • Solid programming ability in C++ or Python, with experience building and debugging software on Linux.

  • Some exposure to the product side of software: web front-ends, APIs, databases, or data pipelines. Having built something other people actually used counts for more than the specific stack.

  • Comfortable working in Linux and with Git.

  • Interest in autonomy, robotics, aerospace, or space.

Perks & Benefits

  • Competitive compensation

  • Work on flight-grade autonomy software with industry leaders

  • Fast-paced, high-impact environment with genuine ownership

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