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Executive Nvidia Engineering Jobs in Nevada (NOW HIRING)

... NVIDIA to AMD), and enterprise sales cycles * Collaborate with Product and Engineering to translate ... Contribute to board and executive level reporting on customer metrics. Required Experience

Technical Program Manager

Las Vegas, NV · On-site

$123K - $159K/yr

Translate complex technical tradeoffs into clear business implications for executive leadership and ... Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical ...

Technical Program Manager

Las Vegas, NV · On-site

$123K - $159K/yr

Translate complex technical tradeoffs into clear business implications for executive leadership and ... Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical ...

Executive Nvidia Engineering information

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 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 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 most commonly searched types of Nvidia Engineering jobs in Nevada?

The most popular types of Nvidia Engineering jobs in Nevada are:

What are popular job titles related to Executive Nvidia Engineering jobs in Nevada?

For Executive Nvidia Engineering jobs in Nevada, the most frequently searched job titles are:

What cities in Nevada are hiring for Executive Nvidia Engineering jobs?

Cities in Nevada with the most Executive Nvidia Engineering job openings:

Infographic showing various Executive Nvidia Engineering job openings in Nevada as of June 2026, with employment types broken down into 57% Full Time, 31% Part Time, and 12% Contract. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution.

Head of Customer Experience

SupportFinity™

Las Vegas, NV • On-site

$200 - $250/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


Key responsibilities

  • Build and lead TensorWave's customer organization to ensure customer satisfaction, retention, and expansion.

  • Design and optimize the customer journey from evaluation through deployment, renewal, and expansion.

  • Partner with internal teams and customers to translate feedback into product and infrastructure improvements.


Job description

Our mission at Tensorwave Cloud is to build seamless, secure, reliable, and resilient AI infrastructure at scale, eliminating barriers and challenging the status quo to empower builders and support AI innovation.

About The Role

We’re seeking a Head of Customer Experience to build and lead TensorWave’s customer organization as we scale our AMD-powered AI infrastructure platform.

You will own customer satisfaction, retention, and expansion across AI startups, ML teams, and Fortune 500 customers.

This is a senior leadership role responsible for building high-performing customer teams, establishing scalable customer success processes, and serving as an executive sponsor for strategic accounts running large-scale training and inference workloads.

You will partner closely with company leadership, develop strong C-suite relationships, and ensure customer success becomes a durable, measurable function as TensorWave grows.

Responsibilities
  • Define and execute TensorWave's hypergrowth customer operations strategy
  • Build, mentor, and scale a high-performing organization of technical customer success managers and operations professionals
  • Design and optimize the customer journey from POC/evaluation through production deployment, scaling, renewal, and expansion.
  • Lead quarterly business reviews and strategic planning sessions with customer Engineering stakeholders
  • Act as voice of the customer within TensorWave, advocating for needs related to AMD GPU performance, ROCm software stack, platform features, and infrastructure scaling
  • Proactively identify at-risk enterprise accounts based on utilization patterns, support tickets, or competitive pressures and orchestrate recovery strategies
  • Develop and lead customer advisory boards, executive forums, and industry working groups to strengthen TensorWave's position in the AI infrastructure ecosystem
  • Recruit, develop, and retain top-tier customer success talent with strong technical backgrounds in AI/ML infrastructure, GPU computing, and cloud platforms
  • Design scalable processes, runbooks, and best practices for managing enterprise customers with diverse workloads (LLM training, inference, fine-tuning, HPC)
  • Implement robust performance management frameworks with clear metrics around customer health, GPU utilization, expansion pipeline, and NRR
  • Deploy and optimize customer success platforms integrated with usage analytics, GPU telemetry, and business intelligence systems
  • Partner with Sales on seamless handoffs, technical account planning, competitive displacement strategies (NVIDIA to AMD), and enterprise sales cycles
  • Collaborate with Product and Engineering to translate customer feedback on AMD GPU performance, ROCm compatibility, platform features, and infrastructure needs into roadmap priorities
  • Build strong partnerships with Sales, Product, Marketing, Engineering, Operations, and within the broader AMD ecosystem.
  • Contribute to board and executive level reporting on customer metrics.
Required Experience
  • Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
  • 7+ years of experience in customer success, enterprise account management, or solutions engineering roles in cloud infrastructure, GPU computing, or AI/ML platforms
  • 5+ years of people management experience, including managing managers and building high-performing teams from scratch
  • Proven track record leading customer success at scale in high-growth infrastructure or platform companies
  • Strong technical fluency with cloud computing, GPU architecture, and AI/ML workload
  • Ability to engage credibly with customer ML engineers and infrastructure teams
  • Exceptional executive presence with ability to engage and influence C-level and VP-level engineering/technical stakeholders
  • Strategic thinker with strong business acumen, analytical capabilities, and data-driven decision-making approach
  • Outstanding communication and presentation skills with ability to inspire teams, influence cross-functionally, and represent TensorWave at industry events
  • Experience building scalable CS operations, implementing health scoring systems, and establishing data-driven customer engagement models
  • Track record of recruiting, developing, and retaining high-performing teams in competitive talent markets
Preferred Experience
  • MBA or advanced technical degree (MS in CS, ML, or related field)
  • Hands-on experience with GPU computing (AMD Instinct, NVIDIA A100/H100) and understanding of AI/ML training and inference workloads
  • Familiarity with AMD ROCm ecosystem, PyTorch, TensorFlow, HuggingFace, and LLM training/fine-tuning workflows
  • Experience in neocloud, alternative cloud providers, or companies disrupting incumbent markets
  • Background in technical pre-sales, solutions architecture, or DevOps/ML engineering
  • Experience managing customer relationships during platform migrations or competitive displacement scenarios (especially NVIDIA to AMD transitions)
  • Strong network in AI/ML, cloud infrastructure, or HPC communities
  • Prior experience at high-growth startups that scaled from Series A to IPO or acquisition
What We Bring
  • Mission driven company
  • Competitive Salary
  • Stock Options
  • 100% paid Medical, Dental, and Vision insurance
  • Flexible PTO
  • Paid Holidays
  • 401(k)
  • Parental Leave
  • Flexible Spending Account
  • Short Term Disability Insurance
  • Life and Voluntary Supplemental Insurance
  • Mental Health Benefits through Spring Health

We’re looking for resilient, adaptable people to join our team, people who believe in the mission and think at massive scale. The solutions that worked on a handful of devices will not work at Exascale. Be prepared to be pushed daily, to learn a lot, and literally build the future.

Tensorwave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, national origin, or veteran status.

About the company

TensorWave

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