AI Infrastructure and Frameworks Intern, Cosmos Lab - 2027
Core
Develop training and post-training systems for advanced Physical AI models, including world foundation models and robot policies, connecting training, inference, and evaluation with simulation and real-world robot interaction.
Role type
Intern, AI Infrastructure Engineer
Builds
Training infrastructure, RL infrastructure, simulation/robotics integration pipelines, and evaluation systems for Physical AI
Domain
AI Infrastructure, Physical AI, Robotics, High-Performance Computing
Deliverable
infrastructure
Required skills
Python, distributed execution, memory management, data movement, training infrastructure, RL infrastructure, simulation/robotics integration, inference infrastructure, profiling, benchmarking, performance modeling
Preferred skills
C++/CUDA development, GPU profiling, distributed parallelism, low-precision training, compute–communication overlap, scheduling, placement, resource allocation, data transfer optimization, open-source contributions, research in ML systems
Technologies
Python, C++, CUDA, NVIDIA GPU infrastructure
Responsibilities
Develop and optimize training infrastructure for advanced Physical AI world models; Build Physical AI post-training and RL infrastructure supporting advanced training algorithms; Improve efficiency and scalability across training, inference, simulation, and evaluation; Analyze and optimize system performance using profiling, benchmarking, and performance modeling
Seniority
Intern
