ML Engineer, Agents & Reasoning
Clera
<h3>About the Role</h3><p style="min-height:1.5em">We 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.</p><p style="min-height:1.5em">As an <strong>ML Engineer, Agents & Reasoning</strong>, 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 <strong>Berlin, Germany</strong> (on-site).</p><p style="min-height:1.5em"><em>Please note: visa sponsorship is not available for this role.</em></p><h3>What You'll Do</h3><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Design and implement agentic systems that plan, reason, and act across real materials discovery workflows.</p></li><li><p style="min-height:1.5em">Build decision-making systems that operate over experiments, simulations, and scientific datasets.</p></li><li><p style="min-height:1.5em">Select next actions under uncertainty and encode when autonomy should act versus when a human should stay in the loop.</p></li><li><p style="min-height:1.5em">Implement planning, control logic, and uncertainty-aware decision-making tailored to physical systems and lab environments.</p></li><li><p style="min-height:1.5em">Encode operational, experimental, and safety constraints directly into agent behavior.</p></li><li><p style="min-height:1.5em">Define stopping criteria, fallback strategies, and recovery mechanisms to prevent brittle behavior.</p></li><li><p style="min-height:1.5em">Collaborate with AI researchers to embed predictive models into agent workflows and translate model outputs into executable actions.</p></li><li><p style="min-height:1.5em">Integrate agents with laboratory automation and software systems so agent outputs drive real-world actions.</p></li><li><p style="min-height:1.5em">Instrument agents with logging, monitoring, and diagnostics to support observability and debugging.</p></li><li><p style="min-height:1.5em">Build evaluation frameworks that assess decision quality, learning efficiency, and system behavior — beyond simple model accuracy.</p></li><li><p style="min-height:1.5em">Analyze failure cases and iterate on system design based on real-world experimental outcomes.</p></li><li><p style="min-height:1.5em">Own systems end-to-end: from prototype through deployment and ongoing operation.</p></li></ul><h3>What We're Looking For</h3><p style="min-height:1.5em"><strong>Required</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">4–8 years of experience building ML-driven or algorithmic decision-making systems in production or applied research settings.</p></li><li><p style="min-height:1.5em">Strong background in scientific or structured data modeling (rather than language-first or NLP-heavy systems).</p></li><li><p style="min-height:1.5em">Experience with planning, control, optimization, probabilistic reasoning, or decision-making under uncertainty.</p></li><li><p style="min-height:1.5em">Proficiency in modern ML frameworks such as <strong>PyTorch</strong> or <strong>JAX</strong>, paired with strong general software engineering skills.</p></li><li><p style="min-height:1.5em">Comfortable owning systems end-to-end, from early prototype through to reliable production operation.</p></li><li><p style="min-height:1.5em">Ability to reason clearly about system behavior in complex, partially observable environments.</p></li><li><p style="min-height:1.5em">Clear communicator who can collaborate effectively across AI, engineering, and scientific teams.</p></li><li><p style="min-height:1.5em">English fluency (additional language skills a plus).</p></li></ul><p style="min-height:1.5em"><strong>Nice to Have</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Technical curiosity about physical systems, laboratory experiments, and real-world constraints.</p></li><li><p style="min-height:1.5em">Experience in materials science, chemistry, cleantech, or adjacent scientific domains.</p></li><li><p style="min-height:1.5em">Familiarity with laboratory automation or robotics integration.</p></li><li><p style="min-height:1.5em">Additional European language skills (German in particular).</p></li></ul><h3>Location & Work Arrangement</h3><p style="min-height:1.5em">This role is <strong>on-site in Berlin, Germany</strong>. We work closely as a team in person, and we expect this role to be based full-time at our Berlin office. <em>Visa sponsorship is not available.</em></p><h3>Why This Role</h3><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Work on genuinely hard AI problems at the frontier of scientific discovery and physical-world autonomy.</p></li><li><p style="min-height:1.5em">Join an early-stage, mission-driven team where your work directly shapes both the product and the culture.</p></li><li><p style="min-height:1.5em">Collaborate across AI research, engineering, and laboratory science in ways that are rare in a single role.</p></li><li><p style="min-height:1.5em">Contribute to technology with meaningful real-world impact in the energy transition and advanced manufacturing.</p></li></ul><p>Find more <a href="https://www.arbeitnow.com/english-speaking-jobs">English Speaking Jobs in Germany</a> on Arbeitnow</a>