ML Engineer, Agents & Reasoning

About the RoleWe are a seed-stage deeptech startup at the intersection of AI, robotics, and materials science, building an advanced platform that dramatically accelerates the discovery of new materials — particularly for the energy sector. Our work combines physics-informed AI, autonomous laboratory systems, and rich multi-modal experimental data to compress decades-long R&D timelines into years. As an ML Engineer, Agents & Reasoning, you will design and build the agentic AI systems that sit at the heart of our materials discovery workflows. You'll turn predictive models into reliable, operational decision-making agents that work alongside physical experiments, robotic systems, and scientific datasets. This is a high-ownership, end-to-end role on a small, cross-functional team of ~12–60 people based in Berlin, Germany (on-site). Please note: visa sponsorship is not available for this role. What You'll Do• Design and implement agentic systems that plan, reason, and act across real materials discovery workflows. • Build decision-making systems that operate over experiments, simulations, and scientific datasets. • Select next actions under uncertainty and encode when autonomy should act versus when a human should stay in the loop. • Implement planning, control logic, and uncertainty-aware decision-making tailored to physical systems and lab environments. • Encode operational, experimental, and safety constraints directly into agent behavior. • Define stopping criteria, fallback strategies, and recovery mechanisms to prevent brittle behavior. • Collaborate with AI researchers to embed predictive models into agent workflows and translate model outputs into executable actions. • Integrate agents with laboratory automation and software systems so agent outputs drive real-world actions. • Instrument agents with logging, monitoring, and diagnostics to support observability and debugging. • Build evaluation frameworks that assess decision quality, learning efficie