ML Researcher, Representation Learning

Skip to main contentEnglishEnglishBack to all jobsML Researcher, Representation LearningBerlinFull-timePermanent employeeApply for this jobYour missionInvent 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 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 structureDecide what information should be explicit, implicit, or learnedBuild abstractions that transfer across tasks and domainsBuild multi-modal foundation models Combine graphs, sequences, text, images, simulations, and experimental dataExplore how different modalities reinforce or contradict each otherMove beyond benchmark metrics toward models that support real decisionsWork where research meets reality Test ideas in production-grade systems used by scientistsCollaborate closely with chemists, physicists, and automation teamsLearn quickly which ideas hold up and which don’tPush representation learning forward Introduce probabilistic reasoning and uncertainty awarenessChallenge existing paradigms when they break down in physical domainsHelp shape the broader direction of AI-native science at DuniaYour profilePhD or equivalent training in machine learning, computer science, or a closely related quantitative field, with4–8 years of post-degree experience in research-driven ML rolesDeep experience in representation learning and modern deep learning architecturesTrack recordof designing representations for structured or scientific data that generalize beyond a single task or datasetStrong software engineering skills, with experience turning research ideas into robust, maintainable systemsComfortable working at the boundary ofresearch and production, theory and engineeringCurious about the physical world and motivated by applying ML to chemistry, physics, or materialsWilling to challenge existing paradigms when they break down in real-world settingsFluent in English; additional language desirableAbout usDunia, 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 videoWe 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!Apply for this job