Partner with AI-native founders and engineering teams to design, optimize, and scale AI platforms on NVIDIA technologies, focusing on agentic systems, AI copilots, and multimodal AI.
Compensation
expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Serve as a trusted technical advisor to the next generation of AI-native companies building category-defining applications such as developer copilots, AI search engines, agentic platforms, and multimodal creative tools.
Work directly with startup founders and engineering teams to architect and optimize AI workloads using NVIDIA technologies including CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NVIDIA NeMo, NIM microservices, and GPU-accelerated data processing frameworks.
Help AI-native companies scale training and inference infrastructure, optimizing model performance, cost efficiency, and latency across NVIDIA accelerated computing platforms.
Guide startups through complex architectural decisions including model optimization, inference scaling, agent frameworks, multimodal pipelines, and real-time AI systems.
Collaborate closely with NVIDIA engineering, research, product, and go-to-market teams to identify emerging AI-native categories and influence NVIDIA’s platform roadmap.
Requirements
BS/MS degree or equivalent experience in Computer Science, Engineering, or a related field
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Serve as a trusted technical advisor to the next generation of AI-native companies building category-defining applications such as developer copilots, AI search engines, agentic platforms, and multimodal creative tools.
Work directly with startup founders and engineering teams to architect and optimize AI workloads using NVIDIA technologies including CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NVIDIA NeMo, NIM microservices, and GPU-accelerated data processing frameworks.
Help AI-native companies scale training and inference infrastructure, optimizing model performance, cost efficiency, and latency across NVIDIA accelerated computing platforms.
Guide startups through complex architectural decisions including model optimization, inference scaling, agent frameworks, multimodal pipelines, and real-time AI systems.
Collaborate closely with NVIDIA engineering, research, product, and go-to-market teams to identify emerging AI-native categories and influence NVIDIA’s platform roadmap.
Requirements
BS/MS degree or equivalent experience in Computer Science, Engineering, or a related field
Nice to have: building or scaling AI-powered products