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How much do nvidia data scientist jobs pay per year?

As of Jun 14, 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 NVIDIA data scientist?

The average salary for an NVIDIA data scientist ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Entry-level positions may start lower, while experienced data scientists with expertise in machine learning and deep learning tools can earn higher salaries. Benefits often include stock options and performance bonuses.

Are data scientists still in demand?

Data scientists remain in high demand across various industries due to the increasing reliance on data-driven decision making and AI technologies. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and roles often require knowledge of tools such as TensorFlow or Hadoop.

What degree is needed for NVIDIA jobs?

For a Data Scientist position at NVIDIA, a bachelor's degree in computer science, data science, statistics, or a related field is typically required, with many roles preferring or requiring a master's or Ph.D. for advanced positions. Strong skills in programming, machine learning, and data analysis tools are also essential. Relevant experience and proficiency in programming languages like Python or R can enhance candidacy.

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.

How hard 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 interview rounds assessing technical expertise and problem-solving abilities.

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 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.

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Nvidia Data Scientist jobs near you
Senior System Software Engineer, Enterprise MODS

Senior System Software Engineer, Enterprise MODS

NVIDIA

Santa Clara, CA • On-site

Full-time

Posted 21 days ago

Job description

Job Summary:
NVIDIA is a leading company in AI, HPC, and cloud computing, seeking a Senior System Software Engineer for their Enterprise MODS team. The role involves developing diagnostic systems for data center platforms, leading integration efforts, and mentoring engineering teams while driving innovation in diagnostics for complex server systems.
Responsibilities:
• Develop diagnostic systems for NVIDIA data center platforms, which involve hardware and software tools to develop the worst case stress workloads for CPUs, GPUs, memory, storage, and interconnects.
• Lead platform bring-up and integration, ensuring diagnostics are embedded early and effectively across the server lifecycle.
• Drive hardware validation strategy in collaboration with architecture and hardware teams, crafting robust validation plans for new server generations.
• Analyze root causes of complex failures, acting as a Level 2 engineering contact for critical issues and offering scalable solutions across the stack.
• Develop diagnostics software to ensure quality and performance at scale across ODM and partner production lines.
• Mentor and grow engineering teams, providing technical leadership and encouraging a culture of innovation and excellence.
• Influence the long-term strategy by developing diagnostic architecture and roadmaps for the upcoming products of NVIDIA and its partners.
Qualifications:
Required:
• Proven experience architecting diagnostics for complex server systems, especially at the SW/HW interface.
• Deep systems knowledge: x86/ARM architectures, Linux/Windows OS internals, firmware (UEFI/BIOS), BMC, and platform security.
• Ability to weigh tradeoffs in system development and drive the most optimum solutions with customers and multi-disciplinary teams.
• Expertise in programming languages like C, C++, and Python for tool development and automation.
• Familiarity with high-speed interconnects such as PCIe, Infiniband, NVLink, and Ethernet.
• Strong communication skills to engage with technical and executive team.
• BS/MS or equivalent experience in Computer Science, Electrical Engineering, or related field.
• 12+ years of engineering experience in diagnostics, embedded systems, or cloud platforms.
Preferred:
• Experience driving diagnostics across rack-level or cluster-level deployments.
• Background in cloud-scale infrastructure and partner engagement.
• Demonstrated success in influencing product direction and vendor roadmaps.
• Passion for mentoring and building high-performing teams.
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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