AI Engineer – Human-to-Robot Learning (human)

About the role

\n\nYour Mission & Challenges • Model the Human Experience: Turn multimodal, body-worn data into representations a robot can learn from. • Bridge Two Bodies: Solve cross-embodiment transfer, translating human motion and interaction into action spaces a robot with a completely different body can use. • Build Foundation Models That Act: Design pretraining and fine-tuning strategies for robotic foundation models. • Prove It Works: Build the benchmarks that separate models that merely mimic from models that generalize. • Shape What Gets Captured Next: Turn model blind spots into sharp, concrete requirements for data capturing devices. • Cross-Functional Collaboration: Work shoulder to shoulder with hardware and systems engineering teams while staying laser-focused on the data and AI side. What We Can Look Forward To • Master's or PhD in Computer Science, Machine Learning, Robotics, or comparable. • Real, hands-on experience with multimodal foundation models (VLA, video-action, or similar). • Experience with cross-embodiment transfer, RL based retargeting. • Deep understanding of low-level robotics control. • Strong grounding in imitation learning, representation learning, and self-supervised learning across sensor modalities. • Fluency in modern machine learning frameworks and large-scale training infrastructure. • A communicator who moves easily between researchers, engineers, and hardware teams. • Fluent English, German a plus.