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Executive Nvidia Engineering Jobs (NOW HIRING)

Deloitte

Channel Sales Manager, NVIDIA Focus

San Jose, CA · On-site

$178K/yr

The NVIDIA Channel Sales Manager will bring strong alliance relationship management, project ... Engineering leadership, alliance leaders, industry sales executives, and Account Principals ...

Nvidia

OR · On-site

... engineering teams to help them design, build, and deploy accelerated AI solutions using NVIDIA ... executives. * Proven ability to structure and implement complex technical engagements, negotiate ...

Nvidia

OR

... and executive audiences. Ways to Stand Out from the crowd: * Deep familiarity with NVIDIA ... engineering teams are rapidly growing. If you're a creative and autonomous person with a real ...

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Executive Nvidia Engineering information

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$26.5K

$93.6K

$184K

How much do executive nvidia engineering jobs pay per year?

As of Jun 5, 2026, the average yearly pay for executive nvidia engineering in the United States is $93,552.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $120,500.00 per year, depending on experience, location, and employer.

What is the difference between Executive Nvidia Engineering vs Nvidia Hardware Engineer?

AspectExecutive Nvidia EngineeringNvidia Hardware Engineer
Required CredentialsBachelor's or Master's in Engineering, Business, or related fields; leadership experienceBachelor's or Master's in Electrical, Computer, or Hardware Engineering; technical certifications
Work EnvironmentLeadership meetings, strategic planning, cross-department collaborationDesign, testing, and development of hardware components in labs or offices
Employer & Industry UsageUsed in corporate leadership, product strategy, and high-level project management within NvidiaUsed in R&D, product development, and technical implementation teams at Nvidia

Executive Nvidia Engineering roles focus on strategic leadership, project oversight, and high-level decision-making, often requiring management experience. Nvidia Hardware Engineers concentrate on designing and testing hardware components, requiring technical expertise. Both roles are integral to Nvidia's success but differ significantly in responsibilities and work environment.

What are the key skills and qualifications needed to thrive as an Executive Nvidia Engineer, and why are they important?

To thrive as an Executive Nvidia Engineer, you need advanced expertise in computer engineering, deep learning, and GPU architecture, typically supported by a relevant engineering degree and extensive industry experience. Proficiency with programming languages like C++ and Python, experience with CUDA, and familiarity with AI frameworks such as TensorFlow or PyTorch are crucial, as are potential certifications in cloud or AI technologies. Leadership, strategic thinking, and strong communication skills are vital for driving innovation and leading high-performance teams. These skills and qualities ensure the effective development and deployment of cutting-edge technologies while aligning technical initiatives with organizational goals.

What does an Executive Nvidia Engineering professional do?

An Executive Nvidia Engineering professional typically leads engineering teams and oversees technical projects at Nvidia, focusing on innovative solutions in areas such as graphics processing, artificial intelligence, and high-performance computing. They are responsible for setting technical vision, managing large-scale engineering operations, and aligning projects with the company's business goals. Additionally, they collaborate closely with other executives, stakeholders, and partners to drive strategic initiatives and ensure product excellence. Their role requires deep technical knowledge, leadership skills, and the ability to operate in a fast-paced, cutting-edge technology environment.

How does an Executive Nvidia Engineering role typically collaborate with cross-functional teams within the company?

In an Executive Nvidia Engineering position, collaboration with cross-functional teams is central to driving innovation and meeting business objectives. Executives often work closely with product managers, software and hardware engineering teams, research scientists, and business development leaders to align technical projects with strategic goals. They facilitate communication between technical and non-technical stakeholders, ensuring that engineering efforts support product roadmaps and customer needs. This role frequently involves leading cross-departmental meetings, resolving technical challenges, and mentoring team leads to foster a culture of collaboration and high performance.
What cities are hiring for Executive Nvidia Engineering jobs? Cities with the most Executive Nvidia Engineering job openings:
What are the most commonly searched types of Nvidia Engineering jobs? The most popular types of Nvidia Engineering jobs are:
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Executive Nvidia Engineering jobs near you
Infographic showing various Executive Nvidia Engineering job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 84% Physical, 8% Hybrid, and 8% Remote job distribution, with an average salary of $93,552 per year, or $45 per hour.
Developer Relations Manager, AI Platform and Tools - Data Platform Engineering

Developer Relations Manager, AI Platform and Tools - Data Platform Engineering

NVIDIA

Santa Clara, CA • On-site

Full-time

Posted 6 days ago

Job description

Job Summary:
NVIDIA is a leading technology company specializing in AI and accelerated computing platforms. They are seeking a Developer Relations Manager to lead strategic engagement within the AI platform and tools ecosystem, partnering with companies in data platform engineering to enhance the adoption of NVIDIA technologies.
Responsibilities:
• Develop and maintain deep technical expertise in data platform engineering, serve as the trusted technical advisor for ISVs and startups building in that space.
• Understand partner workloads and accelerate adoption by integrating the NVIDIA software stack including libraries, SDKs, NIMs, and blueprints, into partner products and data pipelines, delivering measurable performance and scalability improvements.
• Drive partner onboarding and co-innovation through technical enablement assets such as reference architectures, sample code, benchmark, and workshop content that accelerate deployment of production-ready solutions.
• Engage with partner technical leaders to guide best-practice integrations, solve complex architectural challenges, and establish structured collaboration cadences that surface emerging workflows and inform NVIDIA product and platform strategy.
• Build and expand a strategic ecosystem of AI platform and tools partners, track ecosystem and technology trends, and identify opportunities to scale NVIDIA adoption and ecosystem growth.
• Collaborate cross-functionally with solution architects, engineering, product management, and accounts teams to strengthen partner engagement and optimize adoption strategies.
• Advocate for ecosystem technical requirements by channeling actionable feedback from field deployments into NVIDIA product and engineering roadmaps.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 5+ years of experience in the technology industry across software engineering, developer relations, technical partnerships, solutions architecture, or product management, including 3+ years of hands-on experience in AI.
• Deep domain knowledge across enterprise data platform, including data engineering and pipeline acceleration, post-training data preparation and curation, data pipeline for RAG and semantic search.
• Proven ability to lead complex, multi-stakeholder technical engagements, align cross-functional priorities, and drive execution across internal teams and external partners.
• Excellent communication and stakeholder management skills, with the ability to explain complex technical concepts to both engineering and executive audiences.
Preferred:
• Experience architecting, integrating, and scaling joint solutions with strategic ISVs or ecosystem partners is preferred.
• Deep familiarity with NVIDIA’s accelerated AI stack, RAPIDS, NeMo Curator, NeMo Data Designer, NeMo Retriever, cuDF, cuML, cuGraph, cuVS and other frameworks and CUDA-X libraries, with experience integrating them into production platforms.
• Experience partnering with early-stage or high-growth startups/ISVs in fast-paced, ambiguous environments.
• A strong builder mindset, with a track record of creating technical solutions, enablement assets, or ecosystem integrations from the ground up.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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