Full-Time

CUDA Python Technical Product Manager

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$168k - $327.8kAnnually

+ Equity

Senior, Expert

Santa Clara, CA, USA

Remote option available, but primary location is Santa Clara, CA.

Category
Product Management
Product
Software Engineering
Required Skills
Python
CUDA
Product Management
Machine Learning

You match the following NVIDIA's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • BS, or MS in Computer Science, Computer Engineering, or a similar field, or equivalent experience.
  • 6+ years of experience in product management, technical project management, or similar roles in the technology industry.
  • Solid understanding of GPU computing, CUDA, and Python programming.
  • Experience working with developers, open-source communities, or technical users to gather feedback and drive product improvements.
  • Excellent communication and interpersonal skills with a strong ability to influence cross-functional teams.
Responsibilities
  • Define the product vision, strategy, and roadmaps for CUDA Python.
  • Collaborate with internal CUDA engineers, Python core developers, and key team members to deliver a seamless Python-to-CUDA experience.
  • Engage with the open-source community, understand their needs, and translate those into product features that improve the developer experience.
  • Ensure the integration of CUDA Python aligns with other key NVIDIA technologies.
  • Identify and prioritize use cases for CUDA Python across industries like machine learning, scientific computing, and deep learning.
  • Work with developer relations and marketing teams to craft a go-to-market strategy, positioning CUDA Python as a critical tool for developers, scientists, and researchers.
  • Analyze market trends and customer feedback to make data-driven decisions on product features and improvements.
Desired Qualifications
  • Experience working on new technologies, particularly with Python and GPU computing, and bringing them to market.
  • In-depth knowledge of CUDA, Python libraries for numerical computation (such as NumPy, SciPy, or cuPy), and GPU-accelerated machine learning frameworks like TensorFlow or PyTorch.
  • Familiarity with compiler technologies, JIT compilation, and performance optimization for high-performance computing.
  • Passion for driving community engagement and improving developer tools.

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 main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA stands out from competitors by offering a combination of hardware and software solutions, including cloud-based services like NVIDIA CloudXR and NGC, which enable scalable applications in AI and machine learning. The company's goal is to drive innovation in technology and provide advanced solutions that cater to a wide range of clients, from gamers to enterprises.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of VinBrain enhances NVIDIA's AI-driven healthcare solutions.
  • Investment in Nebius Group boosts NVIDIA's AI infrastructure capabilities.
  • Partnership with Serve Robotics aligns with NVIDIA's focus on robotics and AI applications.

What critics are saying

  • Increased competition from AI startups like xAI challenges NVIDIA's market position.
  • Serve Robotics' rapid expansion may lead to financial strain if market growth lags.
  • Integration challenges from VinBrain acquisition may affect NVIDIA's operational efficiency.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
  • The Omniverse platform enhances NVIDIA's capabilities in industrial AI and digital twins.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Company Equity

401(k) Company Match