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Nvidia Machine Learning Jobs in Texas (NOW HIRING)

Nvidia Corporation

Senior Compiler Engineer - AI

Austin, TX · On-site

$121K - $160K/yr

The ideal candidate brings broad experience across machine learning, including reinforcement ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

Senior Developer Technology Engineer - AI

Austin, TX · Hybrid

$54 - $71.25/hr

... in deep learning, machine learning or other AI domains. * Work directly with other technical ... NVIDIA's success in the advancement and availability of Artificial Intelligence has created ...

NVIDIA

Solutions Architect, Supercomputing

Austin, TX · On-site

$62.50 - $82.25/hr

Published record of thought leadership in a technical area or industry segment - Deep Neural Network, Machine Learning R&D - Agentic AI, surrogate Models, or foundation models. Company : NVIDIA is a ...

Nvidia

Datacenter GPU Power Architect

Austin, TX

You will help with Performance vs Power Analysis, track ASIC milestones for impactful NVIDIA future product lineup. * Deploy machine learning techniques to develop highly accurate power and ...

Nvidia

Principal SoC Architect - Hardware

Austin, TX

NVIDIA is developing processor and system architectures that are at the forefront of accelerating machine learning, automotive and high-performance computing applications. We are building the most ...

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Nvidia Machine Learning information

See Texas salary details

$23.8K

$39.7K

$82K

How much do nvidia machine learning jobs pay per year?

As of Jul 22, 2026, the average yearly pay for nvidia machine learning in Texas is $39,673.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

What is a Nvidia Machine Learning job?

A Nvidia Machine Learning job involves developing and optimizing AI models, deep learning frameworks, and GPU-accelerated applications. Engineers in this role work on cutting-edge research, building scalable ML solutions, and improving performance on Nvidia hardware like GPUs and AI accelerators. They collaborate with software and hardware teams to enhance AI capabilities across industries such as gaming, healthcare, and autonomous systems. Strong coding skills in Python, C++, and experience with ML frameworks like TensorFlow or PyTorch are often required.

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

To thrive in an Nvidia Machine Learning role, a deep understanding of machine learning algorithms, proficiency in programming languages like Python or C++, and a solid background in mathematics or computer science are essential. Experience with Nvidia's CUDA, TensorRT, cuDNN, and familiarity with modern deep learning frameworks such as TensorFlow or PyTorch are highly valued, as are relevant certifications in AI or data science. Strong problem-solving skills, teamwork, and effective communication distinguish top candidates in collaborative, fast-paced environments. These skills are crucial for developing and optimizing AI solutions that leverage Nvidia’s advanced hardware and software platforms.

Does NVIDIA do machine learning?

Nvidia offers extensive tools and platforms for machine learning, including GPUs optimized for training and deploying models. Many machine learning engineers and researchers use Nvidia hardware and software frameworks like CUDA and cuDNN to accelerate AI development. The company also provides AI-focused products and solutions for various industries.

Is it hard to get hired at NVIDIA?

Getting hired for a machine learning role at NVIDIA can be competitive due to the company's focus on advanced technology and innovation. Candidates typically need strong technical skills in deep learning, programming, and relevant experience, along with a solid educational background. The hiring process often involves multiple interviews and technical assessments to evaluate expertise and problem-solving abilities.

What are some common challenges faced by professionals in Nvidia Machine Learning roles?

One common challenge in Nvidia Machine Learning roles is optimizing models to fully leverage GPU architectures for both performance and efficiency, which requires continuous learning as the technology rapidly evolves. Team members often work on complex, large-scale projects that demand close collaboration across software, hardware, and research divisions. Navigating the fast pace of innovation and contributing effectively to cross-functional teams is essential for success. However, these challenges also make the role exciting and offer excellent opportunities for professional growth and hands-on experience with state-of-the-art AI solutions.

Is ML a high paying job?

Machine Learning roles, including positions like Nvidia Machine Learning engineers, are generally well-paid due to high demand for specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and company, but these jobs tend to offer above-average compensation compared to many other tech roles.
What are the most commonly searched types of Nvidia Machine Learning jobs in Texas? The most popular types of Nvidia Machine Learning jobs in Texas are:
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Nvidia Machine Learning jobs near you
Infographic showing various Nvidia Machine Learning job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $39,673 per year, or $19.1 per hour.
Senior Deep Learning Performance Architect

Senior Deep Learning Performance Architect

Nvidia

Austin, TX

$165K/yr

Full-time

Posted 9 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

5th of 215 rated software companies

Job description

We are now looking for a Senior Deep Learning Performance Architect!

NVIDIA is seeking outstanding Performance Analysis Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

What you'll be doing:

  • Develop innovative HW architectures to extend the state of the art in parallel computing performance, energy efficiency and programmability.

  • Benchmark and analyze AI workloads in single and multi-node configurations.

  • Develop high level simulator and analysis tools in C++/Python.

  • Evaluate PPA (performance, power, area) for hardware features and system-level architectural trade-offs.

  • Work closely with peer architecture teams and product management to guide development of the products.

  • Keep abreast with emerging trends and research in deep learning.

What we need to see:

  • MS or PhD in a relevant discipline (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience.

  • 4+ years of experience in parallel computing architectures, interconnect fabrics and deep learning applications.

  • Background in GPU or Deep Learning ASIC architecture evaluation for training and/or inference.

  • Strong programming skills in Python and C++.

Ways to stand out from the crowd:

  • Solid fundamental knowledge in computer architecture and interconnect fabrics.

  • Understanding of modern transformer-based model architectures.

  • Ability to simplify and communicate rich technical concepts to non-technical audience.

  • Have a curious demeanor with excellent problem-solving skills.

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as "the AI computing company", NVIDIA wants you. Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field!

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

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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