Solutions Architect – Accelerated Computing Libraries TPM
Indexed description
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.
- Track and drive joint projects between local SA team and global product teams, ensuring clear ownership, milestones, execution status, and feedback loops from customer engagements to product roadmap decisions.
- Deeply understand customers’ workloads and requirements, and map them to NVIDIA libraries, identifying functional, performance, and usability gaps.
- 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.
- 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.
- 5+ years of experience in the technology industry in roles such as solutions architect, systems engineer, ML engineer, product manager, or software engineer, with a master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields.
- Experience in product management or technical program management, including defining product requirements, managing feature backlogs, coordinating cross-functional teams, and driving projects from concept through delivery.
- Strong interest in accelerated computing, GPU computing, and AI software stacks, with the passion to go deep into new libraries, tools, and frameworks.
- 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 collaboration with global product teams and local customers.
- Track record of owning a product or feature roadmap in an AI/infrastructure software domain — including gathering market and customer insights, prioritizing trade-offs, and translating them into shipped product improvements.
- Background in high-performance computing, distributed training/inference, or large-scale system performance optimization.
- Contributions to open-source projects, technical blogs, or public talks in AI, ML systems, or performance optimization.
- Demonstrated ability to define new problem spaces, propose end-to-end solution architectures, and influence cross-functional teams without direct authority.
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