# Solution Architect – Accelerated Computing Libraries

**Company**: NVIDIA
**Location**: Beijing
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/China-Beijing/Solution-Architect---Accelerated-Computing-Libraries_JR2015847?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_662e7500-7df

## Description

At NVIDIA, our employees are passionate about AI, HPC, and gaming. Our SA team focuses on bringing NVIDIA's new technology into different industries. We help design the architecture of AI computing platforms, analyse AI and HPC applications to deliver value to customers, and focus on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimisation.

**Key Responsibilities:** 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 prioritise 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 analyse industry trends and competitors' solutions, and provide insights on how NVIDIA's libraries should evolve to better meet market and customer expectations.

**Requirements:** 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 the passion to go deep into new libraries, tools, and frameworks. Solid programming skills (such as Python/C/C++), with a good grasp of data structures, algorithms, and computer systems fundamentals; experience reading and understanding complex codebases. Experience working directly with external or internal customers to understand requirements, design solutions, and drive technical adoption. Strong ability to analyse and define problems, quickly learn new technologies, and independently explore and validate solution options. Excellent communication skills: able to explain complex technical concepts clearly to audiences with varied technical backgrounds, and able to structure documents and presentations in a concise and convincing way. Proficiency in written and spoken English and Chinese for collaboration with global product teams and local customers.

**Preferred Qualifications:** Hands-on experience with NVIDIA GPUs, CUDA, and one or more NVIDIA libraries (e.g., MCore, Dynamo, CUTLASS, NCCL) or other AI/HPC frameworks. Background in high-performance computing, distributed training/inference, or large-scale system performance optimisation. Experience conducting performance analysis and benchmarking, defining meaningful KPIs, and driving performance tuning across hardware, libraries, and applications. Contributions to open-source projects, technical blogs, or public talks in AI, ML systems, or performance optimisation. Demonstrated ability to define new problem spaces, propose end-to-end solution architectures, and influence cross-functional teams without direct authority.

## Skills

### Required
- Accelerated computing
- GPU computing
- AI software stacks
- Python
- C/C++
- Data structures
- Algorithms
- Computer systems fundamentals

### Nice to have
- NVIDIA GPUs
- CUDA
- MCore
- Dynamo
- CUTLASS
- NCCL
- High-performance computing
- Distributed training/inference
- Large-scale system performance optimisation

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/China-Beijing/Solution-Architect---Accelerated-Computing-Libraries_JR2015847?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)