Senior NVIDIA Physical AI Engineer / Solution Architect

We are looking for a senior NVIDIA Physical AI Engineer or Solution Architect to support the development of industrial AI solution offerings based on the NVIDIA technology ecosystem. The initial engagement will focus on assessing a broad set of potential industrial use cases and determining which NVIDIA technologies, machine-learning methods and solution architectures are most appropriate. The work will cover areas such as industrial automation, robotics, digital twins, simulation, synthetic data generation and AI-assisted engineering. This is primarily a technical engineering and solution-design role. Other team members will cover project management, commercial strategy and customer-facing consulting. Responsibilities - Assess industrial use cases against the capabilities of the NVIDIA technology ecosystem. - Evaluate relevant technologies, including Omniverse, OpenUSD, Isaac Sim, Isaac Lab and Cosmos. - Select appropriate NVIDIA components and ML approaches for each use case. - Define high-level solution and reference architectures. - Identify data, integration, infrastructure and GPU workload requirements. - Assess technical feasibility, dependencies, risks and implementation complexity. - Help prioritise the strongest use cases for future proofs of concept. - Define the technical scope and roadmap for subsequent PoC and implementation phases. - Provide technically credible input for customer and management presentations. The initial phase will not include building a working prototype. However, we are looking for someone with the technical capability to support or implement subsequent PoCs. Required experience - Strong hands-on experience with NVIDIA technologies, particularly Isaac Sim, Isaac Lab, Omniverse and Cosmos. - Practical experience with robotics simulation, physical AI, synthetic data, digital twins or sim-to-real workflows. - Strong machine-learning knowledge relevant to robotics, computer vision, reinforcement learning or industrial AI. - Experience with Python and ML frameworks such as PyTorch. - Experience designing solutions for industrial automation, manufacturing, automotive, energy, logistics or engineering environments. - Ability to translate an initial use case into a technically feasible architecture and implementation plan. - Previous involvement in real industrial, applied-research or customer implementation projects. - Experience with ROS 2, Isaac ROS, Replicator, GR00T, NVIDIA NIM, OpenUSD, CUDA or industrial engineering systems would be valuable. This is not a general AI, cloud infrastructure, project-management or transformation role. The core requirement is deep NVIDIA and ML expertise combined with the ability to design technically feasible industrial solutions. The engagement is expected to run for approximately four to six weeks at roughly two to three days per week. Successful work may lead to subsequent proof-of-concept and implementation projects. Please begin your proposal by naming the two NVIDIA technologies in which you have the strongest hands-on experience. Include one relevant industrial or applied-research project and clearly describe your personal technical contribution. Generic AI or cloud architecture proposals will not be considered.