NVIDIA

AI computing

SolutionsArchitectAcceleratedComputingLibrariesTPM

$750–1200k ~AI est. Beijing, China FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Solutions Architect – Accelerated Computing Libraries TPM at NVIDIA. Skills: Accelerated computing, AI libraries, HPC libraries, LLM inference, LLM training. Drive adoption of NVIDIA libraries. Work closely with customers”

Industry & Context.

AI computing
Problems you'll solve

Define problems; Explore solution options; Validate solution options

What They're Looking For.

Must Have

5+ years of experience, Master's degree or above, Solid programming skills, Experience working with customers, Ability to analyze and define problems, Excellent communication skills, Proficiency in English and Chinese

Nice to Have

Hands-on experience with NVIDIA GPUs, CUDA experience, Experience with one or more NVIDIA libraries, Experience with other AI/HPC frameworks, Background in high-performance computing, Background in distributed training/inference, Background in large-scale system performance optimization, Experience conducting performance analysis, Experience with benchmarking, Experience defining meaningful KPIs, Experience driving performance tuning, Contributions to open-source projects, Technical blogs contributions, Public talks contributions, Demonstrated ability to define new problem spaces, Demonstrated ability to propose end-to-end solution architectures, Demonstrated ability to influence cross-functional teams

What You'll Do.

Drive adoption of NVIDIA libraries

Work closely with customers

Understand customer workloads

Map requirements to NVIDIA libraries

Identify functional gaps

Identify performance gaps

Identify usability gaps

Design solutions using NVIDIA libraries

Validate solutions using NVIDIA libraries

Develop reference designs

Collaborate with NVIDIA teams

Turn customer needs into product improvements

Build technical assets

Maintain technical assets

Scale NVIDIA libraries

Track industry trends

Analyze competitors' solutions

Provide insights on library evolution

How You'll Work.

Team & Collaboration

Customers' technical teams; Local field teams; Global product teams; NVIDIA product teams; NVIDIA engineering teams; Cross-functional teams

Communication Scope

Explain complex concepts; Structure documents; Structure presentations

Full Job Description

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. **What You’ll Be Doing:** * Drive the adoption of key NVIDIA AI and accelerated computing libraries across multiple industries by working closely with customers’ technical teams, local field teams, and global product teams. * Deeply understand customers’ workloads and requirements, and map them to NVIDIA libraries, identifying functional, performance, and usability gaps. * Design and validate solutions using NVIDIA libraries (e.g., for inference, training, data processing, and simulation), including PoCs, benchmarks, and best-practice reference designs. * Collaborate with NVIDIA product and engineering teams to prioritize and close key gaps through feature requests, performance tuning, and roadmap feedback, turning customer needs into concrete product improvements. * Build and maintain technical assets (sample code, reference implementations, design guides, internal playbooks) that help scale NVIDIA libraries to more customers and use cases. * Track and analyze industry trends and competitors’ solutions, and provide insights on how NVIDIA’s libraries should evolve to better meet market and customer expectations. **What We Need to See:** * 5+ years of experience in the technology industry in roles such as solutions architect, systems engineer, ML engineer, or software engineer, with a master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields. * Strong interest in accelerated computing, GPU computing, and AI software stacks, with

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