Senior Technical Marketing Engineer - AI Inference at Scale 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, TechnologyIndustries

Requirements

BS Degree in Computer Science or Engineering related field with a Masters in Business Administration or equivalent experience in a Product Marketing role
7+ years of experience in product marketing, technical marketing, or customer-facing engineering roles
Passionate about AI/ML workloads at scale
Deep understanding of modern data center architectures, accelerated computing, distributed inference, deep learning frameworks (PyTorch, TensorFlow, JAX), and inference-specific frameworks & optimizations (Triton Inference Server, TensorRT-LLM, vLLM, SGLang)
Experience conducting technical competitive analysis and synthesizing key insights

Responsibilities

Translate NVIDIA’s AI inference and accelerated computing technologies into clear, impactful messaging that resonates with hyperscale data centers and enterprise AI customers
Develop whitepapers, technical blogs, solution briefs, presentations, explainer videos, and demos that highlight NVIDIA’s AI inference capabilities
Work closely with internal teams to deeply understand product features, roadmaps, and competitive differentiators
Analyze competitors’ hardware and software solutions, using data and customer feedback to inform NVIDIA’s positioning
Develop training materials, sales enablement tools, and technical content to empower internal teams, partners, and customers
Partner with campaign marketing, field operations, and partner marketing to ensure seamless product launches and market adoption
Contribute to industry-firsts, customer success stories, analyst briefings, and high-visibility speaking engagements

Skills

Key technologies and capabilities for this role

PyTorchTensorFlowJAXTriton Inference ServerTensorRT-LLMvLLMSGLangDistributed InferenceAccelerated ComputingData Center ArchitecturesAI/MLTechnical Marketing

Questions & Answers

Common questions about this position

What is the salary for this Senior Technical Marketing Engineer role?

This information is not specified in the job description.

Is this position remote or does it require working in an office?

This information is not specified in the job description.

What technical skills are required for this role?

Candidates need a deep understanding of modern data center architectures, accelerated computing, distributed inference, deep learning frameworks like PyTorch, TensorFlow, JAX, and inference-specific frameworks such as Triton Inference Server, TensorRT-LLM, vLLM, and SGLang.

What experience is required for this position?

The role requires 7+ years of experience in product marketing, technical marketing, or customer-facing engineering roles, along with a BS Degree in Computer Science or Engineering related field and a Masters in Business Administration or equivalent experience.

What makes a strong candidate for this role?

Strong candidates have 7+ years in product marketing or technical roles, deep technical expertise in AI inference technologies, passion for AI/ML workloads at scale, and experience in competitive analysis.

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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