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

NEURA Robotics; Riederich; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

NEURA Robotics is seeking a research-focused engineer to advance multimodal foundation models for robot control. You will turn human and sensor data into learnable representations and explore cross-embodiment transfer across robots.

You’ll collaborate with hardware and systems teams, publish benchmarks proving generalization, and shape data-capture requirements for future devices. Fluent English required; German a plus.

Qualifikationen

• Master's or PhD in Computer Science, Machine Learning, Robotics, or comparable.
• 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.

Aufgaben

• Model human experience from multimodal data for robotic learning.
• Bridge two bodies by enabling cross-embodiment transfer.
• Design pretraining and fine-tuning strategies for robotic foundation models.
• Build benchmarks to differentiate generalization from mimicry.
• Define data-capturing device requirements from model blind spots.
• Collaborate with hardware and systems engineering while focusing on data and AI.

Kenntnisse

Multimodal foundation models

Cross-embodiment transfer

Reinforcement learning retargeting

Low-level robotics control

Imitation learning

Representation learning

Self-supervised learning

Modern ML frameworks

Large-scale training infrastructure

Cross-functional communication

English fluency

German language

Ausbildung

Master's or PhD in Computer Science, Machine Learning, Robotics, or comparable

Jobbeschreibung

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.

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.