Technical Marketing Engineer - World Models Physical AI at NVIDIA

Santa Clara, California, United States

Apply Now

Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

BS Degree in Computer Science or Engineering related field or equivalent experience in a technical marketing role (or equivalent experience)
8+ years of experience in technical marketing, developer enablement, or a related technical field with a focus on foundation models use and evangelism
Skilled at translating sophisticated AI concepts into clear, engaging messaging for both technical and business audiences
Strong communication and collaborator leadership skills in matrixed, multi-functional environments
Comfortable with Python and tools like Hugging Face, PyTorch, Docker, or similar for model evaluation, inference, and code-level artifact review (config files, training checkpoints)
Experience developing and improving technical content for corporate and software developer communities previously
Experience running generative AI models - LLMs, diffusion models, or VLMs / VLAs - along with a working understanding of their inputs, outputs, failure modes, and performance bottlenecks

Responsibilities

Develop and deliver technical content: Create and present high-impact, performance benchmark based technical marketing materials to drive enterprise and developer audiences towards adoption of NVIDIA
Core content development: Build whitepapers, technical guides and blogs, videos, demos and solution briefs driving through NVIDIA sales and marketing teams to our partners and customers
Cross-functional teamwork: Collaborate with product, research, and engineering teams to deeply understand features, roadmaps, and differentiators, enabling the creation and delivery of advanced technical materials on large multimodal models, multi-task learning, video networks, generative models, imitation learning, and semi-supervised learning for technical sales teams
Customer and community engagement: Serve as a domain expert on World Models to capture feedback, respond to technical queries, and exhibit world models development and integration workflows and examples
Enable sales & partners: Build training and enablement materials for developer relations teams, partners, and customers
Advance thought leadership: Support industry-firsts, developer success stories, analyst briefings, and speaking engagements

Skills

World Models

Physical AI

Multimodal Models

Multi-Task Learning

Video Networks

Generative Models

Imitation Learning

Semi-Supervised Learning

Technical Marketing

Performance Benchmarks

Whitepapers

Demos

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.

Land your dream remote job 3x faster with AI

Try Jobo Free