Description
Job Overview
You'll build the autonomy brain for a cutting-edge autonomous aerial platform that will take flight. At Helsing, you'll integrate state-of-the-art reinforcement learning agents into the operational systems of their Unmanned Combat Aerial Vehicle (UCAV), the CA-1 Europa.
Responsibilities
- Maintain and improve the existing software stack, including working with internal and external customers to identify issues and improve operational reliability and performance.
- Develop tests and benchmarks, including hardware-in-the-loop (HIL) simulations and flight testing.
- Review code contributions, proposals, and RFCs from colleagues to ensure robustness and adherence to safety and performance standards.
- Propose and implement new features, capabilities, algorithms, infrastructure, or products across the stack.
- Mentor colleagues and support the development of the interviewing pipeline.
- Share experience and technical know-how with other Helsingers.
Requirements
- Write legible, maintainable, and performant code.
- Communicate well in English, both verbally and in writing.
- Collaborate with others, including reviewing code and pair programming.
- Have strong backend or embedded development experience, ideally with a language like Rust, Go, or C++.
- Feel comfortable working with Python in ML-heavy sections of the stack.
Nice to Have
- Experience with Rust and Python specifically.
- Deployment of Reinforcement Learning or Machine Learning agents in real-world systems.
- Safety Programming Experience.
- Familiarity with low-level flight control systems and their interfaces.
- Experience with sensor integration and sensor fusion techniques for navigation.
- Robotics or production ML systems experience.
Benefits
- Competitive compensation and VSOP options.
- Relocation support.
- Social and education allowances.
- Regular company events and all-hands to bring together employees as one team across Europe.
Company Culture
Helsing encourages healthy debates on the use of technology in defence, its benefits, and its ethical implications. They operate at the intersection of machine learning and systems engineering, pushing the boundaries of technical innovation.