NEURA Robotics
Linkedin · Posted 5d ago
AI Engineer – Human-to-Robot Learning (human)
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Indexed description
Your 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.
- 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.
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