Software Engineer, Infrastructure

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, building backend services, data pipelines, and dashboards to accelerate materials discovery.

• Build and maintain backend services in Python (FastAPI, Pydantic) to orchestrate real scientific workflows.
• Develop data pipelines that convert raw experimental output into actionable signals.
• Create internal dashboards and interfaces (React, TypeScript, Tailwind, Streamlit) used daily by scientists and engineers.
• Maintain containerized environments and CI/CD pipelines to keep systems running smoothly.
• Improve observability so teams understand system state proactively — before users report issues.
• Drive reliability improvements grounded in real failure modes and production experience.
• Support job orchestration and ML systems, including integration with SLURM-based simulation clusters.
• Treat infrastructure as a product that directly affects scientific productivity and discovery outcomes.

• 2–5 years of software engineering experience with strong Python fundamentals.
• Practical experience building backend services, preferably with FastAPI and Pydantic.
• Experience with containerized applications and DevOps practices (Docker, Kubernetes, CI/CD).
• Ability to build and maintain data pipelines transforming raw experimental or data-intensive outputs.
• Experience building dashboards and interfaces for technical or scientific users (React, TypeScript, Tailwind, or Streamlit).
• Familiarity with SLURM-based job orchestration or HPC/simulation cluster integration.
• Strong emphasis on observability, monitoring, and production-grade reliability.
• Clear, direct communication skills and a habit of writing clean, maintainable code.
• Authorization to work in Germany without visa sponsorship (sponsorship is not available).
• English fluency; additional languages are a plus.
• Exposure to scientific computing, ML infrastructure, or data-intensive systems.
• Comfort working across the full stack and willingness to dig into unfamiliar territory.
• Background in or familiarity with chemistry, materials science, or life sciences environments.

• Competitive package in line with early-stage deeptech startups at the seed stage, including equity participation.