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Gpu Engineer Jobs in Raleigh, NC (NOW HIRING)

Nvidia

Senior ML Platform Engineer

Durham, NC

$101K - $138K/yr

Our invention-the GPU-functions as the visual cortex of modern computing and is central to ... We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning ...

Contemporaries

Be Seen First

Data Engineer

Durham, NC · On-site

$57 - $63/hr

... Data Engineer to support environmental health and extreme weather research initiatives. This ... Develop and test protocols for GPU-accelerated execution of R- and Python-based models. * Create ...

Nvidia

EDA Workflow Optimization Engineer

Durham, NC · Hybrid

$107K - $127K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... As an engineer in our EDA Workflow Optimization team, you will partner closely with our engineering ...

Nvidia

Senior Developer Technology Engineer - AI

Durham, NC · Hybrid

$52.75 - $69.50/hr

... Engineer, Artificial Intelligence! Would you enjoy researching parallel algorithms to accelerate AI ... In this position, you will research and develop techniques to GPU accelerate workloads in deep ...

Nvidia

Senior ASIC Power Engineer

Durham, NC

Develop innovative HW, GPU and system designs to extend the state of the art performance and efficiency * You are expected to understand the design and implementation, develop power metrics and drive ...

Teledyne

Research Scientist

Durham, NC

Experience with CUDA and GPU programming (strongly desired) * Excellent communication, writing, and interpersonal skills * U.S. Citizenship and the ability to obtain a security clearance What We ...

Teledyne Technologies

Software Engineer

Durham, NC

Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking ... S. in Computer Science, Applied Mathematics, Computer Engineering or Electrical Engineering ...

Teledyne FLIR LLC

Software Engineer

Durham, NC · On-site

Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking ... S. in Computer Science, Applied Mathematics, Computer Engineering or Electrical Engineering ...

Teledyne

Software Engineer

Durham, NC

Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking ... S. in Computer Science, Applied Mathematics, Computer Engineering or Electrical Engineering ...

NVIDIA

Senior ML Platform Engineer

Durham, NC · On-site

$101K - $138K/yr

... GPU clusters. • Apply SRE principles to diagnose, troubleshoot, and resolve complex system issues across the entire stack, ensuring high availability and performance for critical AI workloads. • ...

Teledyne FLIR LLC

Research Scientist

Durham, NC · On-site

Experience with CUDA and GPU programming (strongly desired) * Excellent communication, writing, and interpersonal skills * U.S. Citizenship and the ability to obtain a security clearance What We ...

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Gpu Engineer information

See Raleigh, NC salary details

$37.9K

$98.9K

$133.7K

How much do gpu engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for gpu engineer in Raleigh, NC is $98,911.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,700.00 and $113,200.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior GPU engineers, especially those with extensive experience, specialized skills in graphics architecture, and leadership roles, can earn $500,000 or more annually. High compensation often includes bonuses, stock options, and other incentives, particularly in large tech companies or specialized industries like gaming, AI, or data centers.

What engineers make $300,000 a year?

Senior GPU engineers, especially those with extensive experience, advanced skills in graphics architecture, and expertise in programming languages like C++ and CUDA, can earn $300,000 or more annually. High-level roles in large tech companies or specialized fields such as AI and machine learning often offer compensation at this level, often including bonuses and stock options.

What jobs pay $400 an hour?

High-paying roles for GPU engineers or related specialized tech positions can reach $400 an hour, typically in consulting, freelance, or contract work for companies needing advanced graphics processing or AI hardware development. Such roles often require extensive experience, advanced skills in hardware design, and a strong portfolio, with some professionals earning this rate through independent consulting or in executive technical positions.

What are the key skills and qualifications needed to thrive in the Gpu Engineer position, and why are they important?

To thrive as a GPU Engineer, you need strong knowledge of computer architecture, proficiency in C/C++, and experience with parallel programming models such as CUDA or OpenCL, along with a degree in computer science, electrical engineering, or a related field. Familiarity with debugging tools, driver development, performance profiling utilities, and hardware simulation platforms is typically required. Excellent problem-solving abilities, attention to detail, and effective teamwork and communication skills help distinguish top candidates. These skills ensure that GPU Engineers can develop high-performance solutions, efficiently troubleshoot hardware and software issues, and collaborate successfully in multidisciplinary environments.

What does a GPU engineer do?

A GPU engineer designs, develops, and optimizes graphics processing units and related hardware or software. They work on improving graphics performance, parallel processing, and computational efficiency, often using programming languages like C++ and tools such as CUDA or OpenCL. Their work supports applications in gaming, scientific computing, and machine learning.

What does a GPU Engineer do?

A GPU Engineer designs, develops, and optimizes graphics processing units (GPUs) for applications like gaming, artificial intelligence, and high-performance computing. They work on hardware architecture, driver development, and parallel computing optimizations to maximize performance. GPU Engineers collaborate with software developers, hardware designers, and researchers to improve graphics rendering, machine learning acceleration, and computational efficiency.

What are some common challenges faced by GPU Engineers, and how are they addressed?

GPU Engineers often face challenges such as optimizing code for maximum parallel efficiency, debugging complex hardware-software interactions, and keeping pace with rapidly evolving GPU architectures. Addressing these issues typically requires a combination of deep architectural understanding, use of specialized profiling and debugging tools, and ongoing collaboration with hardware, software, and QA teams. Many companies provide ongoing training and encourage knowledge sharing within engineering teams to help individuals stay current and effectively tackle new technical hurdles. Overcoming these challenges not only sharpens technical expertise but also opens doors for career growth into architect, team lead, or principal engineer roles.

What are the most commonly searched types of Gpu Engineer jobs in Raleigh, NC? The most popular types of Gpu Engineer jobs in Raleigh, NC are:
What are popular job titles related to Gpu Engineer jobs in Raleigh, NC? For Gpu Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Gpu Engineer jobs in Raleigh, NC look for? The top searched job categories for Gpu Engineer jobs in Raleigh, NC are:
Gpu Engineer jobs near you
Senior ML Platform Engineer

Senior ML Platform Engineer

Nvidia

Durham, NC

$101K - $138K/yr

Full-time

Posted 8 days ago

Job description

NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention-the GPU-functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning innovation.

In this role, you will architect, build, and scale our high-performance ML infrastructure using modern Infrastructure-as-Code practices. Your primary focus will be on creating reliable, automated platforms that empower scientists and engineers to train and deploy the most advanced ML models on some of the world's most powerful GPU systems. Join our top team and apply your SRE and software engineering skills to craft robust, user-friendly platforms for seamless ML development.

What You'll Be Doing:

  • Design, build, and maintain our core ML platform infrastructure as code, primarily using Ansible and Terraform, ensuring reproducibility and scalability across large-scale, distributed GPU clusters.

  • Apply SRE principles to diagnose, troubleshoot, and resolve complex system issues across the entire stack, ensuring high availability and performance for critical AI workloads.

  • Develop robust internal automation and tooling for ML workflow orchestration, resource scheduling, and platform operations, with a strong focus on software engineering best practices.

  • Collaborate with ML researchers and applied scientists to understand infrastructure needs and build solutions that streamline their end-to-end experimentation.

  • Evolve and operate our multi-cloud and hybrid (on-prem + cloud) environments, implementing monitoring, alerting, and incident response protocols.

  • Participate in on-call rotation to provide support for platform services and infrastructure running critical ML jobs, driving root cause analysis and implementing preventative measures.

  • Write high-quality, maintainable code (Python, Go) to contribute to the core orchestration platform and automate manual processes.

  • Drive the adoption of modern GPU technologies and ensure smooth integration of next-generation hardware into ML pipelines (e.g., GB200, NVLink, etc.).

What We Need To See:

  • BS/MS in Computer Science, Engineering, or equivalent experience.

  • 5+ years in software/platform engineering or SRE roles, including 3+ years focused on ML infrastructure or distributed compute systems.

  • Strong proficiency in Infrastructure-as-Code (IaC) tools, specifically Ansible and Terraform, with a proven track record of building and managing production infrastructure.

  • SRE-oriented mindset with extensive experience in diagnosing system-level issues, performance tuning, and ensuring platform reliability.

  • Solid understanding of ML workflows and lifecycle-from data preprocessing to deployment.

  • Proficiency in operating containerized workloads with Kubernetes and Docker.

  • Strong software engineering skills in languages such as Python or Go, with a focus on automation, tooling, and writing production-grade code.

  • Experience with Linux systems internals, networking, and performance tuning at scale.

Ways To Stand Out From The Crowd:

  • Experience building or operating ML platforms supporting frameworks like PyTorch or TensorFlow at scale.

  • Deep understanding of distributed training techniques (e.g., data/model parallelism, Horovod, NCCL).

  • Expertise with modern CI/CD methodologies and GitOps practices.

  • Passion for building developer-centric platforms with great UX and strong operational reliability.

  • Proven ability to contribute code to complex orchestration or automation platforms.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

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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