ML Researcher, Representation Learning

Dunia; Berlin; Vor Ort; EUR 80.000 - 100.000; Vollzeit

Benefits dieser Stelle

Inclusive workplace

Opportunities for career growth

Zusammenfassung

An innovative AI company in Berlin is seeking an ML Researcher focusing on representation learning. You will design and implement models for materials discovery, requiring a PhD and experience in ML roles. Collaborating with chemists and physicists, your work aims to enhance AI systems for practical, real-world applications. It's an opportunity to contribute significantly to the intersection of AI and materials science with a diverse and inclusive team committed to impactful research.

Qualifikationen

• 4–8 years of post-degree experience in research-driven ML roles.
• Deep experience in representation learning and its applications.
• Strong software engineering skills for maintainable systems.

Aufgaben

• Design representations for molecules and materials respecting physical structure.
• Build multi-modal foundation models using diverse data types.
• Collaborate with scientists to test ideas in production settings.

Kenntnisse

Representation learning

Deep learning architectures

Software engineering

Probabilistic reasoning

Curiosity about physical sciences

Ausbildung

PhD in machine learning or related field

Jobbeschreibung

Your mission

Invent the representations that make matter legible to machines. Most AI systems succeed because the world they model is forgiving. Materials discovery is not.

At Dunia, we are building AI systems that must reason about molecules, materials, and physical processes across scales, regimes, and sparse data. The limiting factor is not model size. It is representation.

As an ML Researcher, Representation Learning, you work on the hardest layer of AI for Materials: deciding what the machine should see. You invent representations that let models generalize, transfer, and reason under uncertainty, and you test those ideas inside real discovery loops that include experiments and simulations. This role is for someone who wants their representation ideas to matter beyond papers.

Your tasks will include

Define how matter is encoded

• Design representations for molecules, materials, and processes that respect physical and chemical structure
• Decide what information should be explicit, implicit, or learned
• Build abstractions that transfer across tasks and domains

Build multi-modal foundation models

• Combine graphs, sequences, text, images, simulations, and experimental data
• Explore how different modalities reinforce or contradict each other
• Move beyond benchmark metrics toward models that support real decisions

Work where research meets reality

• Test ideas in production‑grade systems used by scientists
• Collaborate closely with chemists, physicists, and automation teams
• Learn quickly which ideas hold up and which don’t

Push representation learning forward

• Introduce probabilistic reasoning and uncertainty awareness
• Challenge existing paradigms when they break down in physical domains
• Help shape the broader direction of AI‑native science at Dunia

Your profile

• PhD or equivalent training in machine learning, computer science, or a closely related quantitative field, with 4–8 years of post‑degree experience in research‑driven ML roles
• Deep experience in representation learning and modern deep learning architectures
• Track record of designing representations for structured or scientific data that generalize beyond a single task or dataset
• Strong software engineering skills, with experience turning research ideas into robust, maintainable systems
• Comfortable working at the boundary of research and production, theory and engineering
• Curious about the physical world and motivated by applying ML to chemistry, physics, or materials
• Willing to challenge existing paradigms when they break down in real‑world settings
• Fluent in English; 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.

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