Technical Marketing Engineer

Nvidia
US, CA, Santa Clara2026-03-12onsite

About the job

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!

Responsibilities

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

Qualifications

Minimum

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

Preferred

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