Software Engineer, Infrastructure

United States Digital Space LLC; Berlin; Vor Ort; EUR 70.000 - 120.000; Vollzeit

Benefits dieser Stelle

Equity participation

Zusammenfassung

United States Digital Space LLC in Berlin, Germany is seeking a backend infrastructure engineer to join a deeptech startup at the intersection of AI, robotics, and materials science. You will build backend services, data pipelines, and dashboards that scientists rely on daily.

This on-site role emphasizes reliability, observability, and usability, with exposure to SLURM-based clusters and containerized environments.

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

Python

FastAPI

Pydantic

Docker

Kubernetes

CI/CD

Data pipelines

React

TypeScript

Streamlit

SLURM

Observability

Communication

Tools

Docker

Kubernetes

CI/CD

Jobbeschreibung

About the Role

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.

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&D timelines in the energy and manufacturing sectors.

What You’ll Do

• 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.

What We’re Looking For

• 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.

Location

This is a full-time, on‑site role based in Berlin, Germany. Candidates must be based in or willing to relocate to Berlin. Visa sponsorship is not available — applicants must have existing authorization to work in Germany.

Compensation & Benefits

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.

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