Technical Program Manager, Capacity at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Semiconductors, Artificial IntelligenceIndustries

Requirements

B.S. (or equivalent experience) in Computer Science or a related technical field
10+ years of experience across software engineering and/or technical program management roles with demonstrated expertise and mastery of technical and management practices
Prior experience developing process and programs focused on the allocation and management of infrastructure resources that span a diverse and large portfolio ($billions)
Prior experience leading programs that span across multiple teams and engineers (100+)
Experience handling large scale HPC and/or AI Infrastructure deployments that stretch across hardware and software
Exceptional communication and presentation skills for diverse technical and non-technical audiences
Strong multitasking abilities with a focus on thoroughness and rapid context switching
Knowledge of agile methodologies and the best in class project management tools
Proactive and enthusiastic in identifying and implementing positive changes in software engineering and release management within a fast-paced environment

Responsibilities

Work across multiple internal customer teams to identify gaps and challenges in capacity allocation - these inputs play a key role in shaping the capacity tooling roadmap
Nurture a culture of continuous improvement, finding new opportunities across tooling, automation and processes to scale overall capacity management
Take lead in defining strategies that will help increase the efficiency and utilization of resources across internal clusters to minimize capacity waste
Guide a diverse set of engineering efforts in an agile program methodology across planning, prioritization, design, dependency management, implementation and execution
Bring a data-first approach to programs (metrics, OKRs, KPIs) to measure program success and for identifying areas of improvement
Create effective communication channels to provide varying audience levels insights into program status, risks and opportunities
Act as an effective technical and non-technical liaison between developers, customers and partners to drive organization alignment across a multi-functional matrixed set of leads

Skills

Agile Methodology

Capacity Planning

Resource Allocation

OKRs

KPIs

Dependency Management

Automation

Tooling

Metrics

Continuous Improvement

Program Management

Infrastructure Management

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

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 products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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