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 - 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., * 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.

Nice to Have:

• 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.

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.