AI & Computer Vision Architect

Required Information Details

Role AI & Computer Vision Architect

Required Technical Skill Set Computer Vision architecture, AI system design, Python, PyTorch, vision pipelines, model training & inference workflows, NVIDIA AI Enterprise-Metropolis, TAO, NIM3Location of Requirement India
Desired Competencies (Technical/Behavioral Competency)Must-Have

• Strong Python programming and ability to design large AI/vision codebases
• End-to-end computer vision system architecture (training validation deployment)
• Experience with vision-based quality inspection in manufacturing / production lines
• Solid understanding of model training, evaluation, optimization, and inference
• Knowledge of synthetic data usage for improving AI model robustness
• Understanding of simulation-based validation and sim-to-real (Sim2Real) concepts
• Ability to integrate AI systems with platform, backend, and data pipelines

Good-to-Have

• Exposure to NVIDIA AI Enterprise
• Exposure to NVIDIA Metropolis (or equivalent vision AI deployment frameworks)
• Exposure to NVIDIA TAO Toolkit (or similar transfer-learning / fine-tuning frameworks)
• Experience with synthetic data generation tools (Omniverse Replicator or equivalent)
• Familiarity with model serving / inference services (NVIDIA NIM or equivalent)
• Experience with edge AI, camera hardware, or industrial vision systems
• Prior exposure to robotics perception or autonomous systems

Role descriptions / Expectations from the Role 1

• Define and own the AI & Computer Vision architecture for Industrial Metaverse solutions
• Establish standards for synthetic data, model training, validation, and deployment
• Guide adoption of NVIDIA Metropolis, TAO, Replicator, and NIM where applicable
• Ensure AI systems are scalable, reliable, and production-ready
• Mentor developers and align AI design with Omniverse and Physical AI teams

Work hands on a guide a team of designers and developers to build use cases associated with NVIDIA Omniverse, Isaac SIM.