Product Marketing Manager - AI Platform Software at NVIDIA

Santa Clara, California, United States

NVIDIA Logo
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI, TechnologyIndustries

Requirements

  • MS/PhD in Computer Science or Engineering or equivalent experience
  • 10+ years of meaningful work experience in a technical marketing role related to deep learning software
  • Technical expertise - Familiarity with popular large language models like DeepSeek, GPT-OSS, Gemma and Phi and an understanding of optimization techniques for accelerating training and inference workloads
  • Frameworks ecosystem knowledge - Experience with compilers such as OAI Triton, XLA, MLIR, and frameworks like PyTorch, JAX, vLLM, sglang
  • Programming skills - Proficiency in modern programming languages like Python
  • Communication skills - Outstanding written and verbal communication and interpersonal skills, with a proven ability to articulate value propositions to both technical and non-technical audiences
  • Project management - Demonstrated ability to prioritize projects, commit to getting things done, and work independently
  • Entrepreneurial approach - A willingness to work on new products and technologies with an entrepreneurial spirit
  • Writing samples - Please include samples of public-facing technical content you’ve built

Responsibilities

  • Build product positions - Collaborate with business leaders across NVIDIA to understand and communicate the value of our products to developers. Gather evidence, develop compelling product claims, and establish positioning points that highlight our strengths and address our competitors' weaknesses
  • Introduce products - Develop and complete well-crafted marketing plans, ensuring consistent messaging across all materials. Collaborate with a diverse cross-functional team, including product management, technical marketing, engineering, campaign managers, and PR, to effectively implement these plans
  • Foster awareness - Segment and target audiences, identify asset gaps, and collaborate with technical teams to build developer-centric marketing content. This includes generating deep technical blogs, webinars, tutorials, and more to showcase the outstanding features and capabilities
  • Public engagement - Represent NVIDIA at trade shows, conferences, and customer meetings. Evangelize and nurture the use of our software development kits to grow the NVIDIA developer community

Skills

Key technologies and capabilities for this role

PyTorchJAXMegatron CoreTensorRT LLMCUTLASSNCCLNIXLProduct PositioningGo-to-Market StrategyTechnical MarketingWhite PapersTechnical PresentationsDeveloper Marketing

Questions & Answers

Common questions about this position

What education and experience are required for this Product Marketing Manager role?

Candidates need an MS/PhD in Computer Science or Engineering or equivalent experience, plus 10+ years of meaningful work experience in a technical marketing role related to deep learning software.

What technical expertise is needed for this position?

The role requires familiarity with popular large language models like DeepSeek, GPT-OSS, Gemma and Phi, an understanding of optimization techniques for accelerating training and inference workloads, experience with compilers such as OAI Triton, XLA, MLIR, and frameworks like PyTorch, JAX, vLLM, sglang, plus proficiency in modern programming languages like Python.

What communication skills are required?

Outstanding written and verbal communication and interpersonal skills are required, with a proven ability to articulate complex technical concepts.

What is the work environment like at NVIDIA?

You'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

What makes a strong candidate for this role?

A strong candidate has the rare blend of both technical and marketing skills, is hard-working and creative, wants to work on state-of-the-art technology, and is passionate about supporting developers.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters
1993Year Founded
$19.5MTotal Funding
IPOCompany Stage
Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries
10,001+Employees

Benefits

Company Equity
401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.
Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.
Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.
NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.
Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.
Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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