First and foremost: We are not a "GPT wrapper" building AI on top of external APIs. At NeuralAgent, we are engineering the foundational layer of autonomous systems, building one of Europe's first Multi-AI-Agent Swarm Operating System. This is Deep Tech with a pulse. You will be collaborating with pioneers in AI, robotics, and aerospace to deploy code that survives in the real world, from contested airspace in defense scenarios to the vacuum of space.
You will join a team trusted by top-tier partners including Airbus, ESA, the European Defence Fund, FCAS, and Ukrainian drone manufacturers. Your contributions will directly power safety-critical, dual-use systems where performance is not just a metric, but a necessity for survival.
What we offer you:
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True Ownership: No micromanagement. We foster a culture of trust where you are the CEO of your domain.
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First-Mover Advantage: Be part of the core team defining a new category in swarm intelligence.
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Shared Success: We offer company shares: be early, contribute to the vision, and own a part of our future growth.
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Student-Friendly Flexibility: We are results-driven and remote-friendly. We respect your academic schedule and support your exams.
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Real-World Impact: Leave the simulation behind. See your algorithms deployed in live drone swarms and space missions.
As a Working Student in our Connectivity & Networks team, you will solve a fundamental challenge in autonomous robotics: maintaining robust connectivity within dynamic drone swarms. You will work to maximize spectral efficiency in complex, contested environments, ensuring our agents stay linked when it matters most. Your role is to bridge the gap between theory and application, transitioning advanced concepts from the lab directly into airborne reality.
You will drive the development lifecycle from the PHY to MAC layers, assisting in the design of advanced beamforming and beam steering techniques and deploying them onto Software-Defined Radio (SDR) platforms. Whether running high-fidelity network simulations or conducting real-world RF experiments, your work will ensure that when our swarm moves, the network adapts, providing critical connectivity for decentralized AI agents across Space, Defense, and Telecoms.
Core Responsibilities:
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Innovate: Support the research and implementation of algorithms for spectral efficiency in autonomous swarms.
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Optimize: Analyze and refine the network stack, specifically focusing on Physical (PHY) and Medium Access Control (MAC) layer performance.
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Validate: Prototype protocols on SDRs (e.g., GNURadio) and validate RF performance through simulation and live flight testing.
To navigate this landscape, you combine academic rigor with a hacker’s mentality. You understand that in wireless communications, the "Physical Layer" is not just a concept; it is a chaotic environment that requires precise engineering. You are currently enrolled in a Master’s or Bachelor’s program in Electrical Engineering, Telecommunications, Information Technology, or Computer Science and are eager to apply your deep understanding of the OSI model to low-level implementation.
You possess an intrinsic understanding of Signal Propagation, Modulation, and Beamforming, and you are ready to translate that knowledge into code. You are not afraid of complexity; you are adept at C/C++ and Rust, and you have likely already tinkered with SDR frameworks or network simulators. Most importantly, you have a "hands-on" mindset: you are driven by the desire to see your algorithms work in the real world, not just in a textbook.
Technical Requirements:
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Core Systems Programming: Proficiency in Rust (Async/Tokio ecosystem, memory safety patterns) and C/C++ for high-performance, low-latency environments.
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Network & RF Engineering: Understanding of the OSI Stack (specifically PHY/MAC layers), wireless concepts (Beamforming, Signal Propagation), and Mesh/MANET architectures.
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Embedded & OS Architecture: Experience with Embedded Linux, the Linux Networking Stack, and real-time system constraints (latency/jitter management).
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Simulation & Tooling: Familiarity with SDR frameworks (GNURadio), network simulators and emulators (NS-3, mininet), or MATLAB/Simulink.
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Edge Intelligence (Bonus): Exposure to integrating AI/ML models on constrained edge devices and decentralized consensus logic.
At NeuralAgent, we are redefining the nervous system of autonomous operations. We engineer dual-use, cloud-free AI-Agent swarms that deliver sovereign, collaborative intelligence across space, air, and ground domains. By decoupling autonomy from centralized clouds, our lightweight, decentralized architecture eliminates decision latency and single points of failure, ensuring persistent mission connectivity even in the most extreme, contested environments. Whether orchestrating resilient satellite constellations, enabling dynamic defense maneuvers, or optimizing self-healing telecommunications networks, our agents provide transparent, certifiable trust and unlimited scalability. We don't just connect systems; we empower them to think, adapt, and act together; securely and autonomously.
