Software Engineer, Infrastructure

DUDE CHEM; Berlin; Hybrid; EUR 65.000 - 90.000; Vollzeit

Zusammenfassung

Dunia is building AI for challenging science problems by turning materials discovery into a programmable discipline. As Software Engineer, Infrastructure, you will own the systems that connect experiments, simulations, and learning components.

You will design robust Python services, orchestrate workflows, and improve data pipelines, observability, and reliability. This role emphasizes practical impact in real-world experimentation and scalable infrastructure.

Qualifikationen

• 2–5 years of software engineering experience.
• Solid Python fundamentals.
• Willing to work across the stack.
• Experience with containerized applications and basic DevOps.
• Clear communication and maintainable code.
• Fluent English; additional languages preferred.

Aufgaben

• Build Python backend services to orchestrate real scientific workflows.
• Develop data pipelines turning raw experimental output into usable signals.
• Create internal dashboards and interfaces for scientists and engineers.
• Maintain containerized environments and CI/CD pipelines.
• Support job orchestration and ML infrastructure; integrate with SLURM-based clusters.
• Make infrastructure decisions informed by real workloads.

Kenntnisse

Python

Cross-stack development

DevOps basics

Clean code

English fluency

Other languages

Tools

React

TypeScript

Tailwind

Streamlit

CI/CD

Docker

SLURM

Jobbeschreibung

Your mission

Build the software backbone lettingAI reason about and experiment on the physical world

Dunia is building AI for one of the hardest unsolved problems in science: turning materials discovery from an academic, trial-and-error process into a programmable, scalable discipline.

At Dunia software doesn’t just serve users, it coordinates robots, experiments, simulations, and learning systems that interact with matter itself.

As Software Engineer, Infrastructure, you will own the systems that make this possible. Your work sits directly between scientific intent and physical execution: if infrastructure is unclear, brittle, or slow, discovery stalls. If it’s well-designed, the entire system accelerates.

This role is for an engineer who wants their software decisions to have real, measurable consequences in the world.

Your tasks will include:

Production systems that matter

• Backend services in Python (FastAPI,Pydantic) that orchestratereal scientificworkflows


• Data pipelines that turn raw experimental output into usable signal

Tools people rely on daily

• Internal dashboards and interfaces (React, TypeScript, Tailwind,Streamlit) used by scientists and engineers


• Systems where usability and correctness directly affect productivity

Infrastructure as a first-class product

• Containerized environments and CI/CD pipelines that keep the system moving


• Observability that tells youwhat’shappening before users complain


• Reliability improvements driven by actual failure modes, not hypotheticals

The full loop: software compute science

• Job orchestration and ML system support


• Integration with SLURM-based simulation clusters


• Infrastructure decisions informed by real workloads, not abstract benchmarks

Your profile

• 2–5 years of software engineering experience, with solid Python fundamentals


• Comfort working across the stack. Youdon'tneed to be an expert in everything, butyou'rewilling to dig into unfamiliar territory


• Experience with containerized applications and basic DevOps practices


• Clear communication and a habit of writing clean, maintainable code


• Bonus: exposure to scientific computing, ML infrastructure, or data-intensive systems


• English fluency,additionallanguages preferred