4 hours ago
Remote, EMEASenior / Staff+
Responsibilities
- Design, implement, train, and evaluate large models and learning algorithms for robotic agents.
- Develop vision-language-action architectures connecting multimodal perception and language understanding with physical control.
- Investigate reinforcement learning and imitation learning methods for challenging objectives.
- Build scalable methods for incorporating demonstrations, teleoperation data, video, simulation trajectories, and robot experience into foundation models.
- Design data-capture methodologies, datasets, evaluation protocols, and data-quality pipelines for embodied learning.
- Develop simulation environments and conduct sim-to-real experiments on physical robotic platforms.
- Explore planning, guided generation, and search over action trajectories for robotic control.
- Prototype capabilities involving dexterous manipulation, mobile manipulation, and whole-body control.
- Write research software and distributed training infrastructure for rapid experimentation.
- Collaborate with research and engineering teams to translate research into reliable real-world systems and communicate results through reports, open-source releases, demonstrations, and publications.
Requirements
- Profound understanding of machine learning, reinforcement learning, or robot-learning foundations.
- Deep expertise in at least one relevant area, such as reinforcement learning, imitation learning, multimodal generative modeling, computer vision, robotics, planning, or control.
- Experience training and evaluating modern deep learning models, including transformer-based or multimodal foundation models.
- Substantial experience training large models across multiple computational nodes.
- Strong software engineering and algorithm-design skills, primarily using Python.
- Deep experience with a modern deep learning framework, primarily JAX.
- Experience designing, executing, and analyzing statistically rigorous machine-learning experiments.
- Ability to formulate research questions, test hypotheses, and draw defensible conclusions.
- Experience iterating across modeling, data, infrastructure, and evaluation.
- Strong communication, leadership, collaboration, technical writing, and research-documentation skills.
- Preferred experience with real-world robots, robotic simulation, manipulation, multimodal sensing, teleoperation, vision-language models, video or world models, deep reinforcement learning, robotics simulators, scalable training, distributed systems, or impactful publications.
- A PhD in Computer Science, Robotics, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience, is preferred.
- Preferred proficiency in contemporary software engineering practices, including version control, testing, code review, and CI/CD.
- Excellent command of English.
Benefits
- Competitive compensation.
- Career growth and learning opportunities.
- Flexibility and ownership.
- Collaborative and innovative culture.
- Opportunity to work on impactful AI projects.
- International environment with talented teams.
Tech Stack
Categories
About Nebius
Nebius builds a full-stack AI cloud offering GPU compute, storage, and tools for training and deploying ML models for startups, enterprises, and research labs. It sells consumption-based cloud infrastructure (IaaS/PaaS) and managed services tailored to generative AI workloads, including large-scale model training and inference. The company is headquartered in Amsterdam and operates as an independent provider.