CUDA Python Technical Product Manager

$148,000 - $287,500/Yr

Nvidia - Santa Clara, CA

Full-time - Mid Level

Santa Clara, CA

Computer and Electronic Product Manufacturing

About the position

The Technical Product Manager for CUDA Python will drive the vision, strategy, and product roadmap to enhance the integration of Python with the CUDA platform. This role focuses on improving the developer experience for Python developers utilizing GPU acceleration, ensuring compatibility with the Python ecosystem, and advocating for user needs within NVIDIA.

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.

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.

Nice-to-haves

• 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.

Benefits

• Highly competitive salaries
• Comprehensive benefits package
• Equity options
• Excellent engineering work culture