Software Engineer, Infrastructure
Summary
Build backend services and data pipelines in Python to orchestrate AI-driven scientific workflows for an autonomous materials-discovery lab.
About the Role
This is an infrastructure engineering role at a seed-stage deeptech startup operating at the intersection of AI, robotics, and materials science. The company builds an autonomous laboratory platform that accelerates the discovery of new materials — particularly for the energy sector — by combining physics-informed AI, advanced algorithms, and real-world experimental data.
As a Software Engineer on the Infrastructure team, you'll be the coordination layer between scientific intent and physical execution. You'll build the backend services, data pipelines, and internal tooling that scientists and engineers rely on every day. Reliability, observability, and usability are treated as genuine product priorities here — not afterthoughts.
What You'll Do
Build and maintain backend services in Python (FastAPI, Pydantic) to orchestrate real scientific workflows.
Develop data pipelines that transform raw experimental output into actionable signals.
Create internal dashboards and interfaces using React, TypeScript, Tailwind, and Streamlit used daily by scientists and engineers.
Maintain containerized environments and CI/CD pipelines to keep systems running smoothly.
Improve observability so teams have visibility into system state before issues surface.
Drive reliability improvements grounded in real production failure modes.
Support job orchestration and ML systems, including integration with SLURM-based simulation clusters.
Treat infrastructure as a first-class product that directly impacts scientific productivity and discovery velocity.
What We're Looking For
Required:
2–5 years of software engineering experience with solid Python fundamentals.
Comfort working across the stack and a willingness to dig into unfamiliar territory.
Experience with containerized applications and practical DevOps skills (CI/CD, Docker, etc.).
Excellent written and verbal communication skills — you'll collaborate closely with both scientists and engineers.
A habit of writing clean, maintainable, well-documented code.
English fluency (additional languages a plus).
Nice to Have:
Exposure to scientific computing, ML infrastructure, or data-intensive systems.
Experience with SLURM, HPC environments, or simulation pipelines.
Background in or curiosity about chemistry, materials science, or physical sciences.
Location & Work Arrangement
This role is on-site in Berlin, Germany. Candidates must be eligible to work in Germany — visa sponsorship is not available.
Why This Role
Work on software that has a direct, measurable impact on scientific discovery timelines.
Join a small, senior team (under 65 people) where your contributions are visible and meaningful.
Operate in a fast-moving deeptech environment combining AI, robotics, and experimental science.
Work alongside colleagues with backgrounds at leading research labs, energy companies, and simulation software firms.