Senior Inference Technical Product Marketing Manager - Accelerated Computing at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, High-Performance Computing, Accelerated ComputingIndustries

Requirements

BS Degree in Computer Science or Engineering or related field, or equivalent experience. Master’s Degree preferred
6+ years of experience in LLM, AI/ML development in an engineering role
5+ years of experience in product management or technical product marketing of AI/ML products
Deep understanding of modern data center architectures
Experience with accelerated computing, distributed inference, and deep learning frameworks (PyTorch, TensorFlow, JAX)
Familiarity with inference-specific frameworks & optimizations (Dynamo, Triton Inference Server, TensorRT-LLM, vLLM, SGLang)
Experience conducting technical competitive analysis and synthesizing key insights
Proven ability to work cross-functionally across engineering, product management, sales, and marketing teams
Strong communication skills, ability to translate technical concepts into clear messaging, and experience creating marketing assets (blogs, whitepapers, presentations, etc.)

Responsibilities

Drive NVIDIA’s inference platform technical go-to-market efforts
Work closely with engineering and product management teams to understand key technical capabilities of the inference stack (GPUs, CPUs, networking, CUDA libraries, model architectures, deployment techniques)
Review and stay up-to-date on model architectures, frameworks, research papers, whitepapers, deployment techniques, and identify intersection points between AI models and NVIDIA’s platform to maximize performance and minimize Total Cost of Ownership (TCO)
Develop crisp, clear positioning, messaging, and assets to highlight NVIDIA’s leadership in inference
Create assets such as blogs, whitepapers, presentations, analyst briefings, and seminars for developer conferences
Closely follow competitive inference announcements and prepare appropriate responses for business and technical/developer audiences
Assist on building keynote slides for executives in areas of subject matter expertise

Skills

PyTorch

TensorFlow

JAX

Triton Inference Server

TensorRT-LLM

vLLM

SGLang

Dynamo

CUDA

GPUs

distributed inference

deep learning frameworks

LLM

AI/ML

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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