NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are building next-generation generative AI systems that create high-quality images, video, 3D, and multimodal media at scale. Our mission is to transform how media content is imagined, generated, edited, and deployed across industries. We are seeking a Technical Marketing Engineer (TME) to lead complex, cross-functional programs spanning research, engineering, product, infrastructure, and release teams, evaluate use cases and marketing content. This role operates at the intersection of frontier generative modeling (diffusion models, multimodal LLMs, video generation), large-scale training systems, and production-grade media deployment. You will drive end-to-end progress — from early-stage research achievements through model release and product integration — ensuring technical rigor, alignment, and operational excellence. If you're interested in a TME role, we'd like to hear from you!
What you'll be doing:
Lead and manage large-scale GenAI initiatives across research, engineering, product, and infrastructure, evaluate use cases and marketing content
Translate ambitious research goals into structured execution roadmaps with clear milestones including GTM
Define program plans and evaluate marketing content across data pipelines, model training, evaluation, safety validation, and release
Partner with research scientists, ML engineers, systems engineers, product managers, and applied teams
Facilitate technical decision-making across trade-offs (model quality vs. scale, cost, latency, and reliability)
Manage complex model training cycles and infrastructure dependencies
Identify and mitigate technical risks early (scalability constraints, data quality issues, inference costs, evaluation gaps)
Provide executive-level program updates and clear status reporting
Lead model release readiness across validation, benchmarking, safety, compliance, and documentation
Establish repeatable processes for rapid iteration without compromising reliability or quality
What we need to see:
Bachelor’s degree from a leading university or equivalent experience
8+ years of experience managing complex technical programs in AI/ML or large-scale systems
Proven ability to operate effectively in ambiguous, research-heavy environments
Track record of delivering cross-functional initiatives on time and at high quality
Ability to reason about trade-offs between model performance, compute cost, scalability, and product requirements
Strong structured thinking and problem decomposition skills
Solid grasp of contemporary generative AI systems (diffusion, multimodal LLMs, video/image creation)
Familiarity with distributed training and large-scale inference systems
Experience working closely with ML research teams
Ways to stand out from the crowd:
Excellent written and verbal communication and collaboration skills to work with world-class teams
Comfortable presenting to senior leadership
High ownership mindset and bias toward clarity and execution
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 160,000 USD - 253,000 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”







