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Nvidia Deep Learning Jobs in Texas (NOW HIRING)

Nvidia

Senior Deep Learning Compiler Engineer

Austin, TX

$103K - $142K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and ...

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Nvidia Deep Learning information

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$10.2K

$78.2K

$130.4K

How much do nvidia deep learning jobs pay per year?

As of Jun 12, 2026, the average yearly pay for nvidia deep learning in Texas is $78,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,100.00 and $129,500.00 per year, depending on experience, location, and employer.

How much does a NVIDIA deep learning performance architect make?

A NVIDIA deep learning performance architect typically earns between $120,000 and $180,000 annually, depending on experience, location, and specific responsibilities. The role often requires expertise in AI frameworks, GPU architecture, and performance optimization. Compensation may also include bonuses and stock options based on performance and company policies.

What is an Nvidia Deep Learning job?

An Nvidia Deep Learning job typically involves working with AI, machine learning, and deep learning technologies to develop, optimize, and deploy neural network models. Employees in these roles may work on GPU acceleration, AI frameworks like TensorFlow and PyTorch, and specialized hardware like NVIDIA GPUs and TensorRT. Positions can range from research scientists and software engineers to AI infrastructure specialists, focusing on improving model performance and scalability. These professionals contribute to cutting-edge AI applications in fields like autonomous vehicles, healthcare, and robotics.

Is ML a high paying job?

Machine learning (ML) roles, including those related to Nvidia deep learning, are generally well-paid due to high demand for specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and certifications, but many ML positions offer competitive compensation compared to other tech roles.

What are the main challenges faced by professionals working in Nvidia Deep Learning roles?

Professionals in Nvidia Deep Learning positions often encounter challenges such as optimizing deep learning models to run efficiently on GPU architectures, keeping up with rapidly evolving AI frameworks, and troubleshooting complex system-level integration issues. They may also need to balance tight project deadlines with the demands of rigorous research and experimentation. Collaboration with interdisciplinary teams—such as software developers, data scientists, and hardware engineers—is common and essential to deliver robust solutions. Overcoming these challenges helps professionals stay at the forefront of innovation in the AI and deep learning industry.

How much does a deep learning engineer make at NVIDIA?

A deep learning engineer at NVIDIA typically earns between $100,000 and $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in AI and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options.

How hard is it to get hired at NVIDIA?

Getting hired at NVIDIA for deep learning roles can be competitive, often requiring strong technical skills in machine learning, deep learning frameworks, and programming languages like Python and C++. Candidates typically need relevant experience, a solid educational background, and a demonstrated ability to work on complex projects. The hiring process may include technical interviews, coding assessments, and behavioral evaluations.

What are the key skills and qualifications needed to thrive in the Nvidia Deep Learning position, and why are they important?

Excelling in an Nvidia Deep Learning role requires a strong background in computer science, machine learning, and mathematics, often supported by an advanced degree in a related field. Expertise in deep learning frameworks (such as TensorFlow or PyTorch), CUDA programming, and experience with Nvidia GPU hardware are typically expected, along with relevant certifications like Nvidia Deep Learning Institute credentials. Strong analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this position. These skills are crucial to efficiently develop, optimize, and deploy deep learning models leveraging Nvidia technologies in cutting-edge applications.

What are popular job titles related to Nvidia Deep Learning jobs in Texas? For Nvidia Deep Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Nvidia Deep Learning jobs in Texas look for? The top searched job categories for Nvidia Deep Learning jobs in Texas are:
Nvidia Deep Learning jobs near you
Infographic showing various Nvidia Deep Learning job openings in Texas as of June 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% In-person job distribution, with an average salary of $78,152 per year, or $37.6 per hour.
Senior Software Architect - Data Center Systems

Senior Software Architect - Data Center Systems

NVIDIA

Austin, TX • On-site

$128K - $174K/yr

Full-time

Posted 29 days ago

Job description

Job Summary:
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. They are seeking a Senior Software Architect to lead software activities for their deep learning server platforms, collaborating with various teams to deliver innovative software solutions.
Responsibilities:
• You will lead software activities for NVIDIA's deep learning server platforms, from design through production; collaborating with teams across company to deliver software solutions
• Drive the system architecture for a complex server platform in a multi-functional environment.
• Partner across application software, libraries, system software and firmware teams to design complete software solutions for new server platforms
• Work directly with major customers to understand their requirements and work to align their roadmap with NVIDIA’s roadmap.
• Work with business partners and vendors to shape their products to meet NVIDIA’s needs.
• Develop a roadmap of new technologies and protocols and drive their design and adoption.
• Mentor architects and engineering teams to grow them into future leaders.
• Make key technical decisions for designs involving complex inter-component dependencies.
Qualifications:
Required:
• Deep experience in designing architecture for scalable and performant server systems, particularly at the SW/HW interface.
• Understanding of HPC or Deep learning workloads and use of accelerated computing platforms.
• Expertise in Out of Band and In-band management architectures.
• Knowledge of server system architecture and implications of architecture decisions on overall performance of end applications.
• Demonstrable experience in implementing left shift strategy to de-risk program execution.
• Excellent written and verbal communication skills.
• BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience.
• 10+ years in the area of System architecture and design.
Preferred:
• Knowledge of cloud and cluster level deployment and management systems.
• Strong background of device management protocols such as Redfish, IPMI, MCTP, PLDM and RDE.
• Knowledge in storage and networking technologies.
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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