Senior Solution Architect – AI Development
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Job Description
NIM Solution Architect designing and optimizing AI workflows using NVIDIA technologies. Collaborating across teams to drive technical projects and customer engagement as an industry leader.
Responsibilities:
- Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions
- Apply NVIDIA NIM Factory Pipeline to package optimized models (including LLM, VLM, Retriever, CV, OCR, etc.) into containers, providing standardized API access for on-prem or cloud deployment
- Refine NIM tools for the community, aiding them in building high-performing NIMs
- Build and implement agentic AI tailored to customer business scenarios using NIMs
- Deliver technical projects, demos, and client support tasks as directed by the Solution Architecture Leadership
- Provide technical support and mentorship to customers, facilitating the adoption and implementation of NVIDIA technologies and products
- Collaborate with multi-functional teams to develop and broaden our AI solutions portfolio
- Be an internal advocate for NVIDIA software and total solutions within the technical community by incorporating NVIDIA technology, especially inference services, into LHA, business partners, and the broader community
- Assist in supporting the NVAIE team and driving NVAIE business in China.
Requirements:
- 5+ years of experience
- Bachelor's or equivalent experience in Computer Science, Artificial Intelligence, or a relevant field
- Proven experience in deploying and optimizing large language models
- Proficiency in at least one inference framework (e.g., TensorRT, ONNX Runtime, PyTorch)
- Strong programming skills in Python or C++
- Familiarity with mainstream inference engines (e.g., vLLM, SGLang)
- Experience with DevOps/MLOps, including Docker, Git, and CI/CD practices
- Excellent problem-solving skills and the ability to solve complex technical issues
- Proven ability to collaborate effectively across diverse, global teams, adapting communication styles while maintaining clear, constructive professional interactions
- Experience in architectural build for field LLM project
- Expertise in model optimization techniques, particularly using TensorRT
- Knowledge of AI workflow development and implementation, and experience with cluster resource management tools.
- Familiarity with agile development methodologies
- CUDA optimization experience and extensive experience in crafting and deploying large-scale HPC and enterprise computing systems.
Benefits:
- NVIDIA leads the computing future, guided by our dedication to innovation and quality.
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