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Nvidia Machine Learning Jobs in Texas (NOW HIRING)

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 ...

Senior Developer Technology Engineer - AI

Austin, TX · Hybrid

$54 - $71.25/hr

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

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give ...

Senior Hypervisor and RTOS Engineer

Austin, TX · On-site

$118K - $156K/yr

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give ...

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 ...

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 ...

Showing results 41-60

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 Sep 5, 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.

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?

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.

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.

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:

What are popular job titles related to Nvidia Machine Learning jobs in Texas?

For Nvidia Machine Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Nvidia Machine Learning jobs in Texas look for?

The top searched job categories for Nvidia Machine Learning jobs in Texas are:

Infographic showing various Nvidia Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Software R&D Engineer, RTL Optimization Tools

Nvidia

Austin, TX • Hybrid

Full-time

Re-posted 24 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA's success builds on a foundation of industry leading hardware. A key strategy in achieving this is our combining of the best of external EDA with highly optimized, internal EDA tools. Our team develops these tools by fusing advances in parallel computing, machine learning, and novel algorithms in C++.

We are seeking an innovative CAD Software Engineer with particular interest in strategies and algorithms for large scale RTL quality, timing, and power optimization. Such optimization usually includes a mix of graph-based algorithms, AI, and feedback from RTL designers, so having experience relevant to each of those areas would be ideal. In practice, techniques often depend on many related domains, so a solid understanding of DFT, clock distribution, power gating, and other SOC integration aspects is essential.

Developing software within a leading hardware company means getting to almost exclusively focus on the latest processes and most advanced designs. We're not bogged down by legacy support, niche roles, or convoluted approval processes. Our developers enjoy unusually high intellectual freedom and the ability to explore broad roles.

If you like to work across many technical areas and see your successes directly realized in the world's best AI hardware, this is it. What you'll be doing: Invent new methods to enable parallel, graph-based RTL traversal, analysis, and manipulation. Devise strategies for rapidly analyzing the impact of RTL changes on data path latency, power, and impact to DFT, clocking, and power delivery.

Explore use of LLMs (Large Language Models), GNNs (Graph Neural Networks), GANs (Generative Adversarial Networks), and Reinforcement Learning for suggesting or automatically implementing RTL modifications. Explore high performance algorithms for clustering, min cost tree covering (technology mapping), datapath implementation and other details of logic synthesis, especially that efficiently incorporate human insight. As with any software engineering team, we do write a lot of code, but this is broader than a typical CAD or EDA role.

Instead, we as a team own the whole process from discovery and invention of new optimization opportunities, to developing solutions and working directly inside design teams to facilitate deployment. That translates to a bigger picture view of your work, going beyond simply responding to user requests to instead actively driving the roadmap of increasing hardware design productivity. What we need to see: MS or PhD in Electrical Engineering or Computer Science or equivalent experience 3+ years of relevant experience in CAD software and VLSI hardware design Demonstrated ability in software development with C++, particularly in algorithm development related to graph traversal, pattern matching, and optimization Familiarity with RTL design, including Verilog and SystemVerilog code, as well as general hardware design concerns such as scan chain insertion, MBIST, clock and power distribution, and bus architectures Familiarity with related EDA techniques, including logic synthesis, global route, static timing analysis, and SAT solvers Strong communication and interpersonal skills Ways to stand out from the crowd: Experience with common EDA building blocks, such as Verific for Verilog parsing, Espresso for logic minimization, and various other components for logic rewriting, tree coverage, SAT solvers, and combinatorial optimization Experience in high performance software design including multithreading, distributed computing, efficient memory and I/O use, etc.

Previous work experience including both software and hardware roles, especially involving SOC/IP integration or RTL design Experience with various machine learning techniques for analysis, optimization, and code generation NVIDIA is widely considered to be one of the technology world's most desirable employers, and due to outstanding advancements, our teams are rapidly growing. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology. If so, we want to hear from you.

#LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 15, 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.


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Benefits

Hours and flexibility

Workplace

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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