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Nvidia Data Scientist Jobs (NOW HIRING)

Nvidia

Senior Data Scientist - Finance

Santa Clara, CA · On-site

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Join NVIDIA as a Senior Data Scientist on our Finance Data Science and AI team, where you will work ...

Winaxis

Data Scientist

Santa Clara, CA · On-site

Data Scientist - Nvidia Santa Clara from day 1 must be on-site 2nd round of interview will be F2F - Onsite at Santa Clara. ANY VISA Must have a strong and active LinkedIn profile. Worked with good ...

Nvidia

NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large ... Scientist to join our team and help advance our capabilities in synthetic data generation for ...

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Nvidia Data Scientist information

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How much do nvidia data scientist jobs pay per year?

As of Jul 8, 2026, the average yearly pay for nvidia data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the salary of a data scientist in NVIDIA?

The average salary for a data scientist at NVIDIA typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in AI and machine learning may earn higher compensation, often including bonuses and stock options.

Is a data scientist job still in demand?

Data scientist jobs remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and the role often offers competitive salaries and growth opportunities.

What is a Nvidia Data Scientist job?

A Nvidia Data Scientist leverages AI, machine learning, and deep learning to develop models and algorithms that optimize GPU-accelerated computing solutions. They work with large datasets, conduct research, and build scalable data-driven solutions for industries like gaming, autonomous vehicles, and healthcare. Their role involves collaborating with engineers and researchers to improve AI frameworks and performance on Nvidia hardware. Proficiency in Python, deep learning frameworks (TensorFlow, PyTorch), and data analytics is essential.

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

To thrive as an Nvidia Data Scientist, you need a solid background in statistics, machine learning, computer science, and typically a graduate degree in a related field. Proficiency with Python, deep learning frameworks (such as TensorFlow or PyTorch), GPU computing, and experience with large-scale data systems are highly valued, along with relevant certifications. Analytical thinking, strong problem-solving abilities, and clear communication are soft skills that set candidates apart in this collaborative, fast-evolving field. These capabilities are essential for driving innovation, building robust AI solutions, and contributing effectively to cross-functional teams at Nvidia.

What are the entry-level jobs at NVIDIA?

Entry-level jobs at NVIDIA for data scientists typically include roles such as Data Analyst, Junior Data Scientist, or Data Science Intern. These positions often require foundational skills in programming, statistics, and machine learning, and may involve working with NVIDIA's AI and GPU technologies. Internships and co-op programs are common pathways for recent graduates to enter the company as entry-level data scientists.

What types of projects do Nvidia Data Scientists typically work on, and how do they contribute to the company's core technologies?

Nvidia Data Scientists are often involved in pioneering projects related to AI model development, computer vision, natural language processing, and deep learning applications optimized for GPU hardware. They collaborate closely with research engineers, software developers, and product teams to create scalable AI solutions that enhance Nvidia’s products, ranging from gaming to autonomous systems. A typical week might involve experimenting with new algorithms, analyzing large datasets, optimizing code for GPU acceleration, and translating research breakthroughs into practical applications. This role offers continuous learning opportunities and plays a direct part in shaping industry-leading technologies.

How difficult is it to get hired at NVIDIA?

Getting hired as a data scientist at NVIDIA can be competitive, requiring strong technical skills in machine learning, deep learning, and programming languages like Python or C++. Candidates often need relevant experience, a solid educational background, and a good understanding of NVIDIA's technologies and products. The hiring process typically involves multiple interviews and technical assessments.
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Nvidia Data Scientist jobs near you
Infographic showing various Nvidia Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Senior Systems Software Security Engineer - Data Center Systems

Senior Systems Software Security Engineer - Data Center Systems

NVIDIA

Remote

Full-time

Posted 15 days ago

Job description

Job Summary:
NVIDIA is searching for a highly motivated, creative engineer with experience in system software security to join the Data Center Systems Software team. In this role, you will focus on securing NVIDIA’s Data Center Systems and delivering security features required for the success of NVIDIA’s Data Center business.
Responsibilities:
• Delivering security features required for the success of NVIDIA’s Data Center business.
• Engaging with NVIDIA teams and partners to drive implementation and deployment of security features and systems.
• Designing, implementing, and delivering innovations to secure AI Data Center systems with focus on Root of Trust (RoT) for boot, attestation, recovery, Out-of-Band management, debug, and overall security firmware development.
• Designing and developing optimized security solutions using and following industry standards such as OpenBMC, UEFI, TCG DICE, SPDM, PLDM, Redfish, NIST SP800-193 and CNSA2.0.
Qualifications:
Required:
• BS or MS degree in Computer Engineering, Computer Science, or related degree (or equivalent experience).
• 5+ years of meaningful software and firmware security engineering experience.
• Excellent comprehension of security fundamentals.
• Experience with software development and lifecycle standards, e.g. threat modeling, unit testing, incident response, code audit, CI/CD etc.
• Experience in python, scripting and system programming.
• Background with modern server architectures.
• Effective written and verbal communication regardless of audience or issue complexity.
• Ability to work collaboratively and remotely with others to accomplish complex goals.
• Solid experience of end-to-end delivery of high-end enterprise servers from definition to customer deployment.
Preferred:
• In-depth familiarity with data center server architecture.
• In-depth understanding of the different deployment models for GPUs (e.g., HPC, AI cluster, single- or multi-GPU servers).
• Experience in Data Center modern networking architectures.
• Contribution to industry open-source security initiatives or standards.
• Experience in Data Center firmware and software management architecture.
• In-depth understanding of the Post-Quantum Cryptography transition.
• Experience in Linux and application security.
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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