<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <strong>About The Role<br/><br/></strong>Join a well-funded deeptech startup at the intersection of AI, robotics, and materials science. This infrastructure engineering role sits at the heart of an autonomous laboratory platform — the coordination layer between scientific intent and physical execution. Your work will directly shape how scientists and engineers discover new materials, with reliability, observability, and usability treated as first-class product priorities.<br/><br/>The company is an early-stage, seed-funded AI-driven materials discovery platform operating in the cleantech and deep science space, with a team of researchers, engineers, and roboticists working toward dramatically accelerating R&amp;D timelines in the energy and manufacturing sectors.<br/><br/>What You'll Do<br/><br/><ul><li>Build and maintain backend services in Python (FastAPI, Pydantic) to orchestrate real scientific workflows. </li><li>Develop data pipelines that convert raw experimental output into actionable signals. </li><li>Create internal dashboards and interfaces (React, TypeScript, Tailwind, Streamlit) used daily by scientists and engineers. </li><li>Maintain containerized environments and CI/CD pipelines to keep systems running smoothly. </li><li>Improve observability so teams understand system state proactively — before users report issues. </li><li>Drive reliability improvements grounded in real failure modes and production experience. </li><li>Support job orchestration and ML systems, including integration with SLURM-based simulation clusters. </li><li>Treat infrastructure as a product that directly affects scientific productivity and discovery outcomes. <br/><br/></li></ul>What We're Looking For<br/><br/><strong>Required:<br/><br/></strong><ul><li>2–5 years of software engineering experience with strong Python fundamentals. </li><li>Practical experience building backend services, preferably with FastAPI and Pydantic. </li><li>Experience with containerized applications and DevOps practices (Docker, Kubernetes, CI/CD). </li><li>Ability to build and maintain data pipelines transforming raw experimental or data-intensive outputs. </li><li>Experience building dashboards and interfaces for technical or scientific users (React, TypeScript, Tailwind, or Streamlit). </li><li>Familiarity with SLURM-based job orchestration or HPC/simulation cluster integration. </li><li>Strong emphasis on observability, monitoring, and production-grade reliability. </li><li>Clear, direct communication skills and a habit of writing clean, maintainable code. </li><li>Authorization to work in Germany without visa sponsorship (sponsorship is not available). </li><li>English fluency; additional languages are a plus. <br/><br/></li></ul><strong>Nice to Have:<br/><br/></strong><ul><li>Exposure to scientific computing, ML infrastructure, or data-intensive systems. </li><li>Comfort working across the full stack and willingness to dig into unfamiliar territory. </li><li>Background in or familiarity with chemistry, materials science, or life sciences environments. <br/><br/></li></ul>Location<br/><br/>This is a <strong>full-time, on-site role based in Berlin, Germany</strong>. Candidates must be based in or willing to relocate to Berlin. <strong>Visa sponsorship is not available</strong> — applicants must have existing authorization to work in Germany.<br/><br/><strong>Compensation &amp; Benefits<br/><br/></strong>Compensation details were not specified in this posting. You can expect a competitive package in line with early-stage deeptech startups at the seed stage, including equity participation.<br/><br/> </div>