Solutions Architect, AI Models is a AI Solutions Architect role (full-time). with NVIDIA Gruppe. in SANTA CLARA, US. Compensation shown: $152K–$242K. Imported listing (source: developer.jobserve.com). Apply on the employer's site (developer.jobserve.com).
Imported listing (source: developer.jobserve.com) · Apply on developer.jobserve.com
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from developer.jobserve.com
NVIDIA is seeking a Solutions Architect to join its AI Software Segment team, helping enterprise customers adopt and deploy NVIDIA AI models and libraries at scale. You will work at the intersection of research and engineering, tackling challenges across the AI model lifecycle from data processing to training, post-training, RL, evaluation, and optimization. The role involves close collaboration with customers and partners on co-design engagements and end-to-end AI solution development.
Responsibilities
Develop end-to-end AI solutions for enterprise use cases using NVIDIA AI models and libraries.
Apply skills across the AI model lifecycle: data processing, orchestration, training, post-training, RL, evaluation, and model optimization.
Support a broad model portfolio including LLMs, multimodal, retrieval, speech, content safety, and edge use cases.
Partner with enterprise customers in co-design engagements to understand data, evaluation criteria, and success metrics.
Contribute to open-source projects, product engineering, publishing findings, and delivering hands-on training.
Requirements
BS, MS, or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, or equivalent experience.
5+ years of experience with AI frameworks such as PyTorch, JAX, or TensorFlow, and libraries like Hugging Face Transformers.
NVIDIA is a technology company that pioneered accelerated computing and the GPU, and is now focused on full-stack AI infrastructure. Its platforms and technologies support artificial intelligence, scientific computing, data science, autonomous vehicles, robotics, and extended/virtual reality.