Dex
AI Research Engineer - Reinforcement Learning
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The role
This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.
If you're interested sign up to Dex to apply.
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This is a defence technology company building AI capabilities for real-time autonomous platforms. They are backed by leading investors, have secured significant funding, and are scaling rapidly across Europe. Their mission is to protect democracies by achieving technological leadership in critical domains, integrating advanced AI with existing hardware to process sensor data in real-time across operational environments.
You will join a core engineering team building the autonomy brain for a flagship autonomous aerial platform. This is end-to-end ownership: developing and integrating state-of-the-art reinforcement learning agents into operational systems that will actually take flight. This isn't theoretical research or simulation-only work; it's about making learned behaviour reliable and robust in safety-critical, real-world deployment, from large-scale simulation training through to flight-ready hardware.
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The work
- Design, train, and deploy state-of-the-art reinforcement learning agents for real-time decision-making on advanced autonomous aerial platforms.
- Own the full RL pipeline: from large-scale distributed simulation environments to integration on flight-ready hardware.
- Develop policies that demonstrate high generalisation and robustness against adversarial conditions in safety-critical operational systems.
- Implement and optimize RL policies for high-performance runtime systems, addressing real-time latency and throughput constraints.
- Contribute to the architecture and deployment of AI software, including testing, QA, and continuous monitoring in production.
What You Bring
- An MSc (or PhD) in Reinforcement Learning, Robotics, or a closely related field, with a strong focus on sequential decision-making.
- Hands-on experience building, training, and deploying RL agents beyond simulation, making learned behaviour reliable in real operational systems.
- Deep familiarity with modern RL and multi-agent RL techniques (e.g., model-free methods, population-based training, handling partial observability).
- Proven ability to integrate RL policies into high-performance runtime systems, understanding real-time latency and throughput constraints.
- Production-grade coding skills in Python, Rust, or modern C++, with experience deploying and monitoring AI software.
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Why apply through Dex
This is a rare role at a company that doesn't advertise widely. Dex helps you cut through the noise and get properly briefed on opportunities like this. Sign up once, and we'll match you to this role and other hard-to-find positions that fit your profile, ensuring you skip the cold-apply process.
If you're interested, sign up to Dex to apply - https://jobs.meetdex.ai/jobs/2352db27-c21f-4ade-b44e-5952e2d113c5
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