Lead research and development of reinforcement learning based autonomous robotics solutions, designing, training and deploying RL controllers for real-world robotic systems.
Locations (2)
Barcelona, Catalonia, Spain
London, England, United Kingdom
Compensation
Competitive salary and VSOP options
Responsibilities
Design and train RL-based controllers for autonomous robots
Integrate vision and sensor fusion for robust control
Develop physics-based simulators and transfer policies to hardware
Ensure safety, efficiency and robustness of deployed policies
Collaborate with cross-functional teams on AI infrastructure
Requirements
MSc or PhD in Robotics, Machine Learning, Control Engineering or related field
Nice to have: PhD with publications in top-tier venues
Nice to have: Experience with dynamic robotic systems
Design, develop, integrate, validate, and deploy AI-enabled robotic applications for industrial and factory automation.
Compensation
The salary range for this role is $153,200 to $234,100.
Responsibilities
Design and deploy robotic applications for industrial automation
Build collision-aware manipulation pipelines
Develop computer-vision and AI perception systems
Integrate AI/ML models into real-time workflows
Develop closed-loop robotic systems
Requirements
Master’s degree in Computer Science, Robotics, Mechanical, Electrical, or Computer Engineering, Artificial Intelligence, Machine Learning, or a related technical field
Nice to have: 5+ years of experience in robotics software
Nice to have: FANUC
Nice to have: Universal Robots
Nice to have: collaborative or industrial manipulators
Join NVIDIA’s Physical AI Technical Marketing team to help developers learn how to build AI systems that perceive and interact with the physical world. Work with engineers and educators to turn robotics and simulation workflows into tested labs, tutorials, and learning experiences. You’ll own a scoped project from a working example through learner testing and publication, helping developers and partners put NVIDIA technology into practice.
Compensation
The expected hourly rate for this position is 20 USD – 71 USD.
Responsibilities
Collaborate with technical marketing, product, engineering, and training teams to design learning content for a selected robotics, simulation, or AI workflow accurately
Build developer-friendly hands-on learning content with clear prerequisites, exercises, expected results, and troubleshooting guidance.
Test tutorials and lab environments from a new learner’s perspective; reproduce failures and work with engineers to resolve them.
Create reusable diagrams, short demonstrations, and knowledge checks that connect technical concepts to practical tasks.
Maintain learning materials in version control, incorporate learner feedback, and document updates so the content stays usable as software changes.
Internship in Physics Simulation team focusing on Newton physics and robotics integration.
Responsibilities
Collaborate with senior robotics and simulation engineers to understand a customer need and develop a Newton core feature or a reusable workflow using Newton.
Take ownership of a scoped contribution from investigation through implementation and evaluation, with guidance, mentoring, and code review from experienced engineers.
Design experiments to demonstrate measurable improvements in correctness, physical fidelity, reliability, performance, or usability using our robotics software stacks and, where appropriate, robotic hardware.
Use AI-assisted development tools to explore approaches, implement and debug code, and validate results.
Contribute tests, documentation, and maintainable software that help users get reliable simulation results and accelerate robot learning.
Requirements
MS or PhD in Computer Science, Robotics, Physics, or a related field
Nice to have: Experience with physics engines such as Newton, PhysX, or MuJoCo
Nice to have: Hands-on experience in robotics, control, robotic manipulation, or machine learning for robotics
Nice to have: Experience with NVIDIA's robotics software stack, such as Isaac Sim and Isaac Lab
Nice to have: Experience with GPU programming and performance analysis using NVIDIA Warp or CUDA
Collaborate with senior robotics and simulation engineers to understand a customer need and develop a Newton core feature or a reusable workflow using Newton
Take ownership of a scoped contribution from investigation through implementation and evaluation, with guidance, mentoring, and code review from experienced engineers
Design experiments to demonstrate measurable improvements in correctness, physical fidelity, reliability, performance, or usability using our robotics software stacks and, where appropriate, robotic hardware
Use AI-assisted development tools to explore approaches, implement and debug code, and validate results
Contribute tests, documentation, and maintainable software that help users get reliable simulation results and accelerate robot learning
Requirements
MS or PhD in Computer Science, Robotics, Physics, or a related field
Nice to have: experience with physics engines such as Newton, PhysX, or MuJoCo
Nice to have: hands‑on experience in robotics, control, robotic manipulation, or machine learning for robotics
Nice to have: experience with NVIDIA's robotics software stack, such as Isaac Sim and Isaac Lab
Nice to have: experience with GPU programming and performance analysis using NVIDIA Warp or CUDA
Skills
Technical Learning Content Development Intern, Physical AI — Summer 2027
Develop and deliver AI learning content for robotics and simulation workflows.
Compensation
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The expected hourly rate for this position is 20 USD – 71 USD.
Responsibilities
Collaborate with technical marketing, product, engineering, and training teams to design learning content for a selected robotics, simulation, or AI workflow accurately
Build developer-friendly hands‑on learning content with clear prerequisites, exercises, expected results, and troubleshooting guidance
Test tutorials and lab environments from a new learner’s perspective; reproduce failures and work with engineers to resolve them
Create reusable diagrams, short demonstrations, and knowledge checks that connect technical concepts to practical tasks
Maintain learning materials in version control, incorporate learner feedback, and document updates so the content stays usable as software changes
Requirements
Bachelor’s or Master’s in Computer Science, Robotics, Electrical Engineering, Computer Engineering, or equivalent program area
Own the product backlog and roadmap for Industrial and Physical AI products, translating stakeholder needs into clear, testable requirements and driving hybrid agile/waterfall delivery.
Responsibilities
Define product roadmap for AI products
Lead stakeholder discovery with global/site teams
Translate needs into user stories, BRDs, FRDs
Run hybrid agile/waterfall delivery model
Maintain prioritized backlog
Requirements
Bachelor's degree in Robotics, Mechatronics, Electrical / Computer Engineering, Computer Science, Construction Management, or related field
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