About Us
STARK is a new kind of defence technology company revolutionizing the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high performance unmanned systems that are software-defined, mass-scalable, and cost effective. This provides our operators with a decisive edge in highly contested environments.
We’re focused on delivering deployable, high-performance systems - not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe - today.
Your mission
Lead the design and deployment of robust GNSS-denied navigation systems for autonomous unmanned platforms operating in contested and degraded environments.
Responsibilities
- Architect and implement navigation frameworks for GNSS-denied and degraded environments
- Develop system-level state estimation pipelines independent of specific sensors
- Implement real-time navigation algorithms in C++
- Integrate navigation systems into ROS2-based autonomy stacks
- Define coordinate frame handling (ECEF, NED, ENU, body frames)
- Handle time synchronization and latency across distributed systems
- Conduct system-level debugging, performance analysis, and validation
- Support simulation, SIL/HIL testing, and real-world flight/field tests
- Produce technical documentation and performance analysis reports
Qualifications
- Proven experience building GNSS-denied navigation systems
- Deep understanding of state estimation and navigation theory
- Strong background in coordinate frames and transformations
- Experience with inertial navigation error modeling
- Expertise in time synchronization and latency handling
- Excellent C++ skills (real-time systems)
- Hands-on experience with ROS2
- Strong debugging, analysis, and reporting skills
Nice to Have- Strong mathematics background (linear algebra, probability, calculus, estimation theory) and/or Physics double major (advantage)
- MATLAB / Python for prototyping, modeling, and analysis
- Experience with simulation and Monte Carlo analysis
- Aerospace, unmanned systems, robotics, or autonomous systems background