Physical AI Engineer - NeuraGym (Aachen) (human)

Your mission & challenges

Own the outcome on the robot: Drive the development of cognitive robotics applications through Physical AI and the NeuraGym platform — you own the outcome on the customer’s robot, not just the model in the repo.

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.

Get models running well on the robot: Take policies from checkpoint to real-time closed-loop control — distillation, quantization, action chunking, latency budgets, and on-device/edge inference under the customer’s cycle time and reliability requirements.

Be the face of NeuraGym for our customers: Be the primary technical contact for customers adopting Physical AI. Build trusted relationships, understand their applications, and accompany them from kickoff to handover.

Hands-on robotics: Work directly on MAiRA, MiPA, LARA, and our humanoid platforms together with multidisciplinary engineering teams — end-effectors and tool changers, sensor selection and mounting, calibration, electrical and fieldbus interfaces, and the mechanical reality of the cell.

Create customer champions: Enable key people at customer organizations to train their own colleagues, so customers become self-sufficient.

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.

Evaluation & reliability: Build the eval harnesses, success-rate benchmarks, and regression tests that decide whether a policy is ready to hand over — and make the failure modes visible before the customer finds them.

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 or PhD in Computer Science, Robotics, Electrical Engineering, or a 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.

Proven experience in customer-facing technical roles (e.g., solution engineering, field AI engineering, technical consulting), including managing several customers in parallel.

Solid understanding of robot hardware — drives and joint modules, torque sensing and encoders, end-effectors, sensor integration, calibration, electrical and fieldbus interfaces (e.g., EtherCAT), and functional safety concepts — enough to tell a model problem from a machine problem on site.

Proven problem-solving abilities, the ability to handle multiple projects in parallel, and a strong bias toward execution and 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 (B2–C1 level).

Willingness to travel frequently to customer sites and NeuraGyms (approx. 40–60%).