Senior Machine Learning Engineer – Robotics AI (VLA / Physical Intelligence) - Remote EU

Location

Remote work, Germany

Job Type

Permanent

Salary

$100000 - $200000 per annum

We are working with a well-funded deep-tech robotics team building next-generation systems that bridge vision, language, and action in the physical world. The focus is on deploying learning-based models directly onto real robotic hardware, moving beyond simulation-heavy research into production-grade embodied AI.

This is a hands-on engineering role for someone who has built and deployed learning systems that interact with the real world - not just trained models in isolation.

What you’ll be working on

• Building and deploying Vision-Language-Action (VLA) and robotics foundation models on real robotic platforms Developing end-to-end learning pipelines from data collection training evaluation • real-world deployment

• Working directly with robotic hardware (manipulation systems / mobile robots depending on project scope)

• Designing large-scale data pipelines from multimodal robot sensor streams (vision, depth, proprioception, action logs)

• Running structured experimentation across architectures, datasets, and training strategies for physical AI systems

• Improving Sim2Real transfer and closing the gap between model performance in simulation and real-world environments

• Optimising inference and latency for real-time robotic control loops

What we’re looking for

• 3 years experience in ML/robotics/computer vision with at least some exposure to real-world robotic systems

• Hands-on experience with VLA, robotics policy learning, RL, imitation learning, or multimodal transformer models

• Experience working across the robotics stack (e.g. ROS, simulation tools such as Isaac / Gazebo / MuJoCo, sensor integration)

• Strong track record of data-driven experimentation (not purely intuition-led iteration)

• Experience building or owning data pipelines for ML systems (collection, filtering, labelling, evaluation)

• Comfortable working close to hardware and debugging real-world system behaviour

• Strong Python and deep learning framework experience (PyTorch preferred)

Nice to have

• Experience deploying models directly onto robots (arms, mobile robots, drones, or similar)

• Exposure to large-scale training (multi-GPU / distributed training)

• Experience with Sim2Real transfer or domain randomisation

• Background in transformer-based robotics policies or foundation models

• Experience with real-time systems or embedded deployment constraints

Why this role is interesting

• You’ll work directly on embodied AI systems operating in the real world, not just simulation research

• High autonomy across model design, data strategy, and deployment

• Opportunity to shape core robotics intelligence systems from the ground up

• Strong focus on shipping systems that work outside the lab

Location / setup Flexible within Europe. Primarily remote working.