Senior ML Engineer (Physical AI)

TL;DR

Senior ML Engineer (Physical AI): Designing and implementing vision-language-action models and learning algorithms for robotic agents with an accent on reinforcement learning and sim-to-real transfer. Focus on scaling multimodal foundation models and integrating perception with physical control in real-world systems.

Location: Remote (Europe) or based in Amsterdam (Netherlands) or the United Kingdom

Company

Nebius is building a full-stack AI cloud platform for the global AI economy, specializing in GPU orchestration and inference optimization.

What you will do

• Design, train, and evaluate large-scale models (VLA) and learning algorithms for robotic agents.
• Develop architectures connecting multimodal perception and language understanding with physical control.
• Build scalable methods for incorporating human demonstrations and simulated interaction data into foundation models.
• Design data-quality pipelines, evaluation protocols, and simulation environments for embodied learning.
• Prototype capabilities in areas such as dexterous manipulation, mobile manipulation, and whole-body control.
• Collaborate with engineering teams to translate research prototypes into reliable real-world systems.

Requirements

• Profound understanding of the theoretical foundations of machine learning, reinforcement learning, or robot learning.
• Deep expertise in multimodal generative modeling, computer vision, robotics, planning, or control.
• Substantial experience training large models across multiple computational nodes.
• Strong software engineering skills in Python and deep experience with JAX.
• Ability to formulate research questions and design statistically rigorous experiments.
• Must be authorized to work in the country of application.

Nice to have

• PhD in Computer Science, Robotics, ML, or AI.
• Experience with robotic simulators such as MuJoCo, Isaac Sim, Isaac Lab, PyBullet, or ROS.
• Knowledge of scalable training techniques like FSDP, ZeRO, FlashAttention, or mixed-precision training.
• Track record of impactful publications or open-source contributions.
• Experience with real-world robots and tactile/force-torque sensing.

Culture & Benefits

• Competitive compensation and career growth opportunities.
• Flexibility, ownership, and a collaborative, innovative culture.
• Opportunity to work on high-impact AI projects in an international environment with talented teams.