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ML Engineer, Agents & Reasoning

Dunia Innovations GmbH
Berlin

Direkt bewerben

Details zur Stelle

Vollzeit

Qualifikationen

Datenmodellierung
Englisch
Forschungserfahrung
Künstliche Intelligenz
Python

Vollständige Stellenbeschreibung

Your mission

Build agentic AI systems that reason, plan, and act inside real materials discovery workflows
Most agent systems live in clean environments: browsers, codebases, or synthetic benchmarks. At Dunia, agents must reason about messy reality: experiments that fail, data that contradicts itself, and physical systems that don’t reset cleanly.

As ML Engineer, Agents & Reasoning, you build the systems that make AI act responsibly inside that reality. You design agents that decide what to do next, use tools intelligently, recover from failure, and know when they don’t know.

Your work sits at the boundary between cognition and control.

Your tasks will include:

Build agentic decision-making systems for discovery

Design and implement agentic systems that plan, reason, and act across materials discovery workflows
Develop agents that operate over experiments, simulations, and scientific datasets, selecting next actions under uncertainty
Define how autonomy is scoped, when humans stay in the loop, and how decisions are escalated

Ground reasoning in scientific and physical reality

Implement planning, control logic, and uncertainty-aware decision-making tailored to physical systems
Encode operational, experimental, and safety constraints directly into agent behavior
Define stopping criteria, fallback strategies, and recovery mechanisms to prevent brittle behavior

Turn models into action

Collaborate closely with AI researchers to embed predictive models into agent workflows
Work with lab, automation, and software teams to connect agents to real experimental and simulation systems
Ensure agent outputs translate into executable actions, not just recommendations

Measure what matters

Build evaluation frameworks that assess decision quality, learning efficiency, and system behavior, not just model accuracy
Analyze failure cases and iterate on system design based on real-world outcomes
Help define what “good decisions” mean in scientific discovery contexts

Ship reliable, production-grade systems

Translate research concepts into robust, maintainable ML systems
Instrument agents with logging, monitoring, and diagnostics for observability and debugging
Take ownership of systems from prototype through deployment and operation

Your profile

4–8 years of experience building ML-driven or algorithmic decision-making systems in production or applied research settings
Strong background in scientific or structured data modeling, rather than language-first systems
Experience with planning, control, optimization, probabilistic reasoning, or decision-making under uncertainty
Proficiency in modern ML frameworks (e.g.PyTorch, JAX) and strong general software engineering skills
Comfortable owning systems end-to-end, from prototype to reliable operation
Able to reason clearly about system behavior in complex, partially observable environments
Technically curious, with interest in physical systems, experiments, and real-world constraints
Clear communicator who can work effectively across AI, engineering, and scientific teams
English fluency;additional language desirable

About us

Dunia, meaning “world” in over 20 languages, reflects our focus on building technologies that deliver abundance globally. By combining physics, AI, and automation, we accelerate materials discovery for next-generation energy and industrial systems. Our work helps make energy more accessible and materials more affordable and resilient while reshaping how science moves from idea to impact. Join us to work on problems where progress truly compounds.

Need more convincing? -> Watch this video

We strive to create a diverse and inclusive workplace where everyone feels welcome and safe to be their authentic self. Non-traditional career paths are welcome and valued. If you share our vision, you can be certain that we want you to succeed. You might be just the right candidate for this or for other roles that have not opened yet.

Reach out, and follow us on LinkedIn!

Direkt bewerben

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