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- Can’t check pay against the visa rules
- No salary stated. Germany EU Blue Card needs at least €50,700 a year (shortage-occupation / recent-graduate: €45,934). Source: https://www.make-it-in-germany.com/en/visa-residence/types/eu-blue-card, rules effective 2026-01-01.
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Sponsorship unknown
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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About the role
At Stark, we forge the future of European and national security through cutting-edge, AI-driven technology and unmatched engineering precision. As a premier defence technology company, our mission is clear: to equip NATO Allies and their partners with next-generation autonomous defence platforms and advanced AI-driven software built to perform in the world’s most demanding environments.
We believe that true security stems from relentless innovation. By combining elite engineering talent with agile technology and an AI-native operational culture, Stark turns complex defence challenges into field-tested, multi-domain solutions.
WHY JOIN US
• The software and systems you work on directly protect personnel and defend European and national sovereignty.
• You will work alongside industry-leading minds on autonomous systems, advanced propulsion, and secure cyber platforms.
• We foster a fast-paced, collaborative environment where bold ideas are supported by serious R&D backing.
About the Team
Minerva is STARK's command and control software — the brain that connects operators to autonomous systems across multiple domains in real time. The Minerva team is a small, senior software group based in Berlin and Munich, working directly with our systems and hardware teams to build mission-critical C2 capabilities deployed in active operational environments.
We move fast, ship real software, and operate under constraints most engineers never encounter — low-bandwidth networks, air-gapped devices, high-stakes decision loops. There is no room for abstraction for its own sake. Everything we build ends up in the hands of real operators in the field.
Your Mission
As a Robotics Engineer with a focus on embedded perception systems, you will play a critical role in enabling real-time autonomy onboard next-generation UAV platforms. You will work directly with camera data pipelines, ROS2-based systems, and embedded compute platforms to build robust, efficient, and scalable perception functionality.
You will contribute as a highly skilled individual contributor—hands-on with the system—bridging diverse codebases and enabling data flows across native ROS2 nodes, legacy frameworks, and containerized third-party modules. Your work will be essential to ensuring that our autonomous systems operate reliably in real-world, resource-constrained environments.
Responsibilities
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Develop and integrate real-time perception pipelines on embedded platforms such as the Jetson Nano NX.
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Migrate legacy monolithic systems to ROS2, refactoring and modularizing components for better scalability and maintainability.
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Enable and optimize image data access across native and containerized components (e.g., Dockerized ROS2 processes).
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Design and implement low-level camera and sensor drivers for real-time vision acquisition.
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Collaborate with AI, controls, and hardware teams to ensure tight integration between perception and other onboard subsystems.
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Profile and debug system performance under embedded constraints (compute, thermal, bandwidth), ensuring stability and robustness in field deployments.
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Contribute to system-level architecture discussions with a focus on communication reliability and modularity.
Required Skills
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Bachelor’s or Master’s degree in Engineering or a related technical field.
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Strong experience with ROS2, including real-world deployment and integration of perception modules.
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Proficient in Python and C++ for embedded and robotics development.
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Solid background in robotics, autonomous systems, embedded development, or aerospace applications.
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Familiarity with embedded Linux platforms, particularly NVIDIA Jetson devices.
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Experience integrating containerized processes (e.g., Docker) into onboard robotic systems.
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Ability to
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