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Nvidia Machine Learning Jobs in Texas (NOW HIRING)

Nvidia

Senior Hardware SoC Architect

Austin, TX · On-site

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

Principal Graphics Developer Tools Engineer

Austin, TX · On-site

$138K - $171K/yr

... machine learning or generative AI techniques to software development workflows. * Contributions to game engines, graphics middleware, graphics SDKs, or open-source graphics projects. NVIDIA is widely ...

Nvidia

Senior Datacenter GPU Power Architect

Austin, TX · On-site

$66.75 - $89.25/hr

Deploy machine learning techniques to develop highly accurate power and performance models of our ... NVIDIA is widely considered to be one of the technology world's most desirable employers. Our ...

Sincera Technologies, Inc.

AI/ML Engineer

Dallas, TX · On-site

... Machine Learning , and model development. * Experience with robotics simulation, reinforcement learning, computer vision , or autonomous systems is highly preferred. * Familiarity with the NVIDIA GPU ...

Nvidia

Senior Software Engineer - Local AI

Austin, TX

$121K - $160K/yr

Understanding modern techniques in Machine Learning, Deep Neural Networks, and Generative AI with ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

Nvidia

EDA Methodology Architect

Austin, TX · Hybrid

$165K/yr

Our team develops these tools by fusing advances in parallel computing, machine learning, and ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

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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 Aug 12, 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:
Nvidia Machine Learning jobs near you
Infographic showing various Nvidia Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Senior Security Engineer, RTOS and Virtualization

Nvidia

Austin, TX • On-site

$113K - $155K/yr

Full-time

Posted 20 hours ago

Posted today

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 243 rated software companies

Job description

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 automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle.

Within NVIDIA DRIVE Software, the Hypervisor and RTOS Team contributes significantly to NVIDIA's advancement in artificial intelligence and autonomous vehicles. Our mission is to manage system resource sharing and separation while fulfilling real-time, safety, and security needs. We design Hypervisor and RTOS focusing on automotive quality, safety, and security required by the real-time, highly reliable system parts of leading Autonomous Vehicles. We are hiring now for the position of Senior Security Engineer, RTOS and Virtualization

What you'll be doing:

  • Lead security engineering for RTOS, hypervisor, and embedded virtualization technologies across design, implementation, review, and verification.

  • Collaborate on CPU and SoC architecture, including privilege levels, memory protection, DMA, interrupts, boot flows, debug controls, and hardware isolation.

  • Build and implement defensive features such as strong partitioning, least-privilege access, secure communication, fault containment, secure updates, and recovery from malicious inputs.

  • Perform threat modeling and automotive TARA, and connect risks, mitigations, requirements, tests, and evidence to security and safety standards.

  • Review low-level C/C++ code, investigate vulnerabilities, build fuzzing and security test infrastructure, and drive fixes into production.

What we need to see:

  • 8+ years of hands-on experience in systems, embedded, platform, product, or automotive security.

  • BSEE/ BSCS degree or equivalent experience

  • Experience securing RTOS, hypervisor, kernel, firmware, boot, driver, or other privileged software.

  • Strong C/C++ skills, with focus on memory safety, concurrency, resource ownership, privilege boundaries, and isolation.

  • Familiarity with CPU and SoC security concepts including MMU/SMMU or IOMMU, DMA, interrupts, boot, debug, and hardware-backed isolation.

  • Experience with threat modeling, vulnerability analysis, exploitability assessment, fuzzing, static or dynamic analysis, and security remediation.

  • Familiarity with automotive cybersecurity, safety, or process standards such as ISO/SAE 21434, UN R155, ISO 26262 interfaces, or Automotive SPICE.

Ways to stand out from the crowd:

  • Drove adoption of Rust, Ada/SPARK, formal methods, or other memory-safe and analyzable systems approaches.

  • Built capability-based or ownership-based security models for low-level systems.

  • Built security automation, fuzzing infrastructure, review agents, or AI-assisted tools used by engineering teams.

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 for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 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.

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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