Accelerated Computing GPU Product Manager
@ NVIDIA

Santa Clara, CA
$268,000
On Site
Full Time
Posted 1 day ago

Your Application Journey

Personalized Resume
Apply
Email Hiring Manager
Interview

Email Hiring Manager

XXXXXXXX XXXXXXXXX XXXXXXXX***** @nvidia.com
Recommended after applying

Job Details

About NVIDIA

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for over 25 years. Today, the company is harnessing the unlimited potential of AI to define the next era of computing, where our GPU acts as the brain for computers, robots, and self-driving cars.

What You'll Be Doing

  • Develop deep understanding of datacenter workloads and applications, especially around Large Language Models for training and inference.
  • Identify customer needs and translate them into compelling GPU product proposals.
  • Collaborate cross-functionally with engineering, operations, sales, and field teams.
  • Create comprehensive go-to-market plans and effective sales collateral.

What We Need To See

Applicants should have 7+ years of experience in technology with a background in product management, AI engineering, design, or development. A degree in engineering, computer science or related field is required (MBA is a plus). The candidate should be capable of understanding GPU, software and computing architectures and be motivated to tackle complex problems while working closely with cloud partners.

Ways To Stand Out

  • Experience with large-scale GPU based AI applications and Large Language Models.
  • Direct involvement in developing or leading cloud computing infrastructures.
  • Proven track record in bringing accelerated computing systems to market.

Key Skills/Competency

  • GPU
  • Product Management
  • AI
  • Machine Learning
  • Data Center
  • Computing Architectures
  • Cloud
  • Go-to-Market
  • Sales Enablement
  • Technical Strategy
Apply without a personalized resume

How to Get Hired at NVIDIA

🎯 Tips for Getting Hired

  • Research NVIDIA's culture: Review mission, values, and recent innovations.
  • Customize your resume: Emphasize GPU and AI product experience.
  • Highlight achievements: Include successful product launches and technical skills.
  • Prepare for interviews: Focus on technical and cross-functional collaboration.

📝 Interview Preparation Advice

Technical Preparation

Review GPU and computing architectures basics.
Study data center and cloud infrastructure trends.
Practice product roadmap and go-to-market planning.
Revisit AI and machine learning application case studies.

Behavioral Questions

Describe a past cross-functional collaboration success.
Explain trade-offs made in complex projects.
Share an experience with tight deadlines in tech.
Discuss a challenge faced during product launch.

Frequently Asked Questions