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Nvidia Data Scientist Jobs (NOW HIRING)

Zefr, Inc

Senior Data Scientist

Marina Del Rey, CA · On-site

$200K - $225K/yr

PyTorch, Triton Inference Server, vLLM, Nvidia Dynamo, Nvidia TensorRT LLM, Weights and Biases ... data science * Hands-on experience fine-tuning large language models (open-source and/or closed ...

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 generating synthetic data and ...

Smarsh

Lead Data Scientist

New York, NY · On-site

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the ... Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo * Knowledge of ...

Smarsh

Lead Data Scientist

New York, NY · On-site +1

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the ... Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo * Knowledge of ...

Smarsh

Lead Data Scientist

Atlanta, GA · Remote

$166K - $214K/yr

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the ... Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo * Knowledge of ...

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Nvidia Data Scientist information

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$165K

$243.5K

How much do nvidia data scientist jobs pay per year?

As of Jul 9, 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 Scientist, Synthetic Data and Privacy

Senior Scientist, Synthetic Data and Privacy

Nvidia

New York, NY • On-site

Full-time

Posted 28 days ago

Job description

NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large language models. We are looking for a Senior Scientist to join our team and help advance our capabilities in generating synthetic data and privacy-preserving AI. You will contribute to open-source libraries within the NVIDIA NeMo ecosystem that enable high-quality synthetic data generation and data privacy at scale, including context-aware anonymization. This role combines hands-on software engineering with applied research in LLMs and privacy-enhancing methods, and you will collaborate with research, engineering, product teams, and external labs.

What you'll be doing:

  • Build LLM-based methods for synthetic data generation, privacy, and context-aware anonymization, with automated evaluation across multilingual text, documents, and multimodal content.

  • Optimize task-specific LLMs for low-latency, high-throughput inference (distillation, quantization), and scale our frameworks to run in real time.

  • Design and maintain open-source libraries and SDKs with clean APIs and strong documentation.

  • Drive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD.

  • Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership.

  • Mentor interns and junior researchers to develop technical growth within the team.

What we need to see:

  • PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.

  • A research background of 2+ years in applied LLM/NLP research and engineering, synthetic data generation, anonymization and PII detection, or related areas. Comparable experience is also considered.

  • Proven track record of developing or maintaining software libraries used by a broad developer community.

  • Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar.

Ways to stand out from the crowd:

  • Active contributions to open-source projects, particularly in ML, security, or privacy domains.

  • Deep technical understanding of LLMs and inference optimization (quantization, distillation, latency/throughput tuning), with frameworks such as vLLM or TGI.

  • Ability to build and optimize scalable data processing pipelines for large-scale models.

  • Functional knowledge of global privacy regulations such as GDPR or CCPA.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 3, and 192,000 USD - 304,750 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 14, 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.
Nvidia logo

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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