Senior Technical Program Manager, GenAI and Models

🔥 1 hour 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 multi-functional programs across training frameworks, evaluation environments, agent and model runtimes, datasets, verifiers, and distributed training infrastructure. • Partner with AI researchers, engineering leaders, product, infrastructure, and QA teams to define roadmaps, achievements, release plans, and measurable success criteria. • Coordinate large-scale RL training and evaluation experiments, including handling GPU resources, dependency tracking, run scheduling, results reporting, release readiness, technical decisions, integration plans, and program updates.

🎯 Requirements

• Bachelor’s degree in computer science, engineering, or a related technical field, or equivalent experience. • 10+ years of technical program management, engineering program management, or related experience delivering sophisticated software platforms. • Experience leading global, matrixed programs across research, software engineering, infrastructure, QA, release teams, and partner groups. • Strong understanding of the AI model lifecycle, including training, post-training, evaluation, experimentation, production readiness, reinforcement learning concepts, and GPU-accelerated distributed systems. • Experience running software releases across repositories, dependencies, test configurations, quality gates, collaborator approvals, open-source workflows, CI/CD systems, and tools such as GitHub, Git, Jira, Linear, Aha!, or Confluence.

🏖️ Benefits

• equity • benefits