Senior Technical Program Manager, Deep Learning Initiatives

🔥 18 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $168k - $258.8k / year

⏰ Full Time

🟠 Senior

🔧 Technical Program Manager

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Lead AI initiatives spanning research, software, hardware, infrastructure, product, quality, security, legal, operations, marketing, and developer relations. • Build roadmaps, achievements, ownership models, governance plans, risk tracking, and success metrics. • Partner with technical teams to align model development, training, inference, evaluation, GPU capacity, and production deployment. • Support architecture and integration decisions while resolving cross-team dependencies. • Share clear updates with leaders on progress, tradeoffs, risks, and recommendations.

🎯 Requirements

• 10+ years of technical program management, engineering program management, software development, or related experience. • Bachelor’s degree in computer science, engineering, or a related technical field, or equivalent experience. • Experience leading strategic programs across multiple business units, engineering teams, geographies, or corporate functions. • Solid understanding of the AI development lifecycle, including model development, training, evaluation, inference, deployment, and support. • Practical experience with deep learning frameworks, GPU-accelerated computing, distributed systems, modern software development practices, agile development, CI/CD, and tools such as Git, GitHub, GitLab, Jira, Aha!, or Confluence. • Experience leading AI platform, infrastructure, developer ecosystem, or product integration initiatives spanning several teams. • Experience working with foundation models, generative AI, multimodal models, agentic systems, or open-source AI communities. • Knowledge of GPU architecture, distributed training, high-performance computing, Kubernetes, workload schedulers, cloud infrastructure, or data-center infrastructure.

🏖️ Benefits

• equity • benefits