Ready to drive transformation in AI models? At NVIDIA, our team focuses on improving community models like Nemotron, Llama, Gemma, DeepSeek, and Qwen. As a Product Manager for Open Models, you will work with groundbreaking technology to accelerate researchers' and developers' success. Join our team known for their dedication to collaboration and outstanding performance.
What you’ll be doing:
Collaborating with community model builders to ensure seamless model support, early access collaboration, and go-to-market alignment.
Tracking emerging trends in the open model space and assess technical differentiators and ecosystem impact of new releases.
Supporting product marketing in crafting model-specific messaging and documentation - including blogs, whitepapers, case studies, and presentations, highlighting NVIDIA’s optimizations and software tools.
Collaborating closely with internal engineering, infrastructure, and developer experience teams to enable best-in-class support for open models across inference, fine-tuning, and evaluation.
Working onsite at least 3 days per week
Facilitating feedback loops between our platform and model builders to continuously improve performance, usability, and compatibility.
Work with executives to launch new products and support keynotes.
What we need to see:
7+ years of significant work experience in product management or technical partner management.
BS or MS or equivalent experience in engineering, computer science, or another technical field. MBA a plus.
Knowledge of the community model ecosystem, including Hugging Face, PyTorch, and inference frameworks like Ollama, SGLang, and vLLM.
Comfortable reviewing Python code used in presentations, demos, and articles.
Experience with creating marketing and social media.
Excellent written and spoken communication skills, including Microsoft products and markdown skills, with the ability to translate between partner requirements and internal priorities.
You love to thrive in a cross-functional organization, by collaborating with peers across teams and functions.
Deep organizational skills, capable of balancing multiple projects at the same time.
Ways to stand out from the crowd:
Product manager experience at a company training frontier AI models.
Hands-on experience with quantization, distillation, or low-rank adaptation techniques and running community models on NVIDIA GPUs.
Hardworking and highly motivated with measurable results (metrics, awards, key accomplishments) you can share.
A growing portfolio of blogs and social posts with links to your relevant work, including technical writing, social media presence, videos, and research papers.
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most hard-working and dedicated people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5.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 an inclusive 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.Skills Required
- 7+ years of work experience in product management or technical partner management.
- BS or MS or equivalent experience in engineering, computer science, or another technical field (MBA a plus).
- Knowledge of the community model ecosystem, including Hugging Face, PyTorch, and inference frameworks like Ollama, SGLang, and vLLM.
- Comfortable reviewing Python code used in presentations, demos, and articles.
- Experience creating marketing and social media content.
- Excellent written and spoken communication skills, including Microsoft products and markdown skills.
- Ability to work onsite at least 3 days per week (hybrid).
- Strong organizational skills and ability to balance multiple projects.
- Product manager experience at a company training frontier AI models.
- Hands-on experience with quantization, distillation, low-rank adaptation (LoRA), and running community models on NVIDIA GPUs.
- Documented measurable results, portfolio of blogs, social posts, technical writing, videos, or research papers.
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.
-
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.
-
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.
-
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.”
