Robotic Foundation Model Engineer Intern (Human)

Your mission & challenges

Drive the development of cognitive robotics applications through Physical AI and the NeuraGym platform.

Training & Fine-tuning cutting-edge models: Take foundation models to production-ready robotic intelligence by executing the full NeuraGym pipeline — including teleoperation, data annotation, training, simulation, deployment, and validation — tailored to real-world robotics applications. Define the data strategy that makes a fine-tune work and own the full post-training loop inlcuding hyperparamter interation, data mixture, LoRA and a honest evaluation.

Hands-on robotics: Collaborate closely with multidisciplinary engineering teams to design, build, and optimize next-generation intelligent robotic systems powered by AI.

Customer Enablement & Support: Guide and onboard users to NeuraGym by reviewing training pipelines and scripts, identifying data quality issues, troubleshooting model behavior, and providing hands-on support to resolve persistent blockers.

Cross-Functional Collaboration: Serve as a key interface between the Cloud and AI teams, ensuring smooth collaboration, technical alignment, and efficient problem-solving across domains.

Product & Research Feedback Loop: Translate field experience and customer insights into actionable feedback for both the NeuraGym product roadmap and the Neura core AI roadmap

What we can look forward to

Master’s degree in Computer Science, Robotics, Electrical Engineering or related field

Hands-on machine-learning experience in robotics - strong in at least one of: vision-based manipulation, reinforcement/imitation learning, or multimodal models - and keen to learn the rest

Demonstrable experience fine-tuning large pretrained models for robotics or another domain: PEFT/LoRA and full fine-tunes, dataset curation, distillation, and evaluation. Familiarity with the open VLA and policy-learning ecosystem (e.g. π0/π0.5, OpenVLA, LeRobot, diffusion policies) is a strong plus

• •Solid Python skills (C++ a plus); practical experience with PyTorch or TensorFlow
• Comfortable working directly with real robot hardware and associated middleware

Cloud experience (AWS, Azure, or GCP) and experience with robotic simulation tools (IsaacSim, MuJoCo, etc.) is a plus

Proven problem-solving abilities and ability to handle multiple projects in parallel

Strong bias toward execution and a high level of personal commitment: you take deployments personally, work through setbacks, and measure yourself by what runs at the customer

Clear communicator who can translate between researchers, engineers and end-users. You have a good command of English and German language (B2 - C1 level)