Solutions Architect – Accelerated Computing Libraries TPM
AI summary of the role
This Solutions Architect role drives adoption of NVIDIA's accelerated computing libraries (e.g., MCore, Dynamo, CUTLASS, NCCL) across industries, focusing on LLM inference/training acceleration and network optimization.
What you’ll do
- Drive adoption of NVIDIA AI and accelerated computing libraries across multiple industries by working with customers, field teams, and product teams.
- Deeply understand customer workloads and map them to NVIDIA libraries, identifying functional, performance, and usability gaps.
- Design and validate solutions using NVIDIA libraries (inference, training, data processing, simulation) including PoCs, benchmarks, and reference designs.
- Collaborate with product and engineering teams to prioritize feature requests, performance tuning, and roadmap feedback.
What you’ll bring
- 5+ years in technology industry as solutions architect, systems engineer, ML engineer, or software engineer with a master's degree or above in CS, math, EE, automation, or related fields.
- Strong interest in accelerated computing, GPU computing, and AI software stacks.
- Solid programming skills in Python/C/C++ with good grasp of data structures, algorithms, and computer systems fundamentals.
- Experience working directly with customers to understand requirements, design solutions, and drive technical adoption.
Technologies
CUDA · MCore · Dynamo · CUTLASS · NCCL · GPU computing · Python · C++ · HPC · LLM inference · distributed training
About NVIDIA
Designs and manufactures GPUs and system-on-chips powering data centers, AI workloads, gaming, autonomous vehicles, and HPC. The foundational hardware for modern deep learning.
Public
Source and classification
Technical pre-sales · Evidence for this classification:
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
More from the 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 l [... source excerpt omitted ...] 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 the passion to go deep into new libraries, tools, and frameworks. Solid programming skills (such as Python/C/C++ [... source excerpt omitted ...] p 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 analyze 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 collaborati
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