(Senior) Robotics AI Engineer – Training & Deployment (Physical AI) (human)

Neura Robotics; Aachen; On-site; EUR 70,000 - 100,000; Full time

Job summary

Neura Robotics’ Neura Gym seeks a Senior Robotics AI Engineer – Training & Deployment to lead data collection, model training, and real-world testing, guiding RoboGym users through the end-to-end training pipeline.

You will coordinate with robotics engineers, support teleoperation and cloud-enabled workflows, review training scripts, and help translate findings into product and AI roadmaps while communicating across researchers, engineers, and end users; strong English and German beneficial.

Qualifications

• Master's degree or equivalent in a technical field and hands-on robotics experience.
• Proven experience in robot learning and embodied AI projects.
• Experience with teleoperation and cloud-based workflows.
• Exposure to robotics simulation tools and cloud platforms.
• Strong problem solving, planning and multi-project management.
• Excellent communication bridging researchers, engineers and end users.
• Proficiency in English; German is beneficial.

Responsibilities

• Serve as hands-on trainer and technical advisor for RoboGym users.
• Onboard users through the NeuraGym workflow including data collection and model training.
• Collaborate with robotics engineers during data collection and demos.
• Review training scripts and resolve learning failures with hands-on support.
• Interface with Cloud and AI teams and ensure timely support.
• Capture lessons learned and feed insights into product roadmaps.

Skills

Robot learning

Physical AI

Embodied AI

Teleoperation

Cloud platforms

Robotics simulation

Project management

Technical communication

English proficiency

German knowledge helpful

Education

Master's degree in Computer Science / Robotics / Electrical Engineering / Artificial Intelligence or related field

Tools

NVIDIA Isaac Sim

MuJoCo

AWS/Azure/GCP

Teleoperation systems

Robotics middleware

Job description

Building the Gyms Where Physical AI Learns to Work

Physical AI can't be trained on the internet. It has to be trained in the real world - through seeing, hearing and feeling real tasks in real environments. That's what NEURA Gym is about: a global network of physical training centers where robots learn industrial skills directly from the people who've mastered them.
As an (Senior) Robotics AI Engineer – Training & Deployment (Physical AI), you will play a key role in enabling robots to learn new skills through data collection, model training, and real-world testing. Working at the intersection of robotics, AI, and user enablement, you will guide customers and internal stakeholders through the complete RoboGym training pipeline, helping transform robotic learning challenges into successful deployments.

Your mission & challenges

• Serve as a hands-on trainer and technical advisor for RoboGym users, designing training curricula, assessing task feasibility, and planning demonstration and data collection sessions for robot skill acquisition.
• Onboard and guide users through the complete NeuraGym workflow, including teleoperation, data annotation, model training, simulation, deployment, and validation.
• Collaborate closely with robotics engineers during data collection and live demonstration sessions to ensure desired robot behaviors and safety standards are achieved.
• Guide users through model training and refinement by reviewing training scripts, identifying data quality issues, helping reproduce and resolve learning failures, and providing hands-on support when persistent blockers arise.
• Act as a trusted interface between users and the Cloud and AI teams, fostering collaboration, facilitating knowledge transfer, and ensuring timely support when needed.
• Capture lessons learned from training engagements and feed insights back into 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, Artificial Intelligence, or a related technical field, or comparable qualifications and practical experience.
• Proven hands-on experience in robot learning, Physical AI, or embodied AI, for example through work with Vision-Language-Action (VLA) models, video-action models or similar.
• Hands-on experience working with robotic hardware, teleoperation systems, and associated middleware in real-world environments.
• Experience with cloud platforms (AWS, Azure, or GCP) and robotics simulation environments such as NVIDIA Isaac Sim, MuJoCo, or similar tools is a plus.
• Strong instructional and problem-solving skills, with the ability to manage multiple training projects in parallel.
• Strong communication skills with the ability to effectively bridge the gap between researchers, engineers, and end users
• Professional proficiency in English, German language skills are beneficial.