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Remote Nvidia Engineering Jobs in California (NOW HIRING)

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

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Remote Nvidia Engineering information

What is a remote Nvidia engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are the key skills and qualifications needed to thrive as a remote Nvidia engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

What are the most commonly searched types of Nvidia Engineering jobs in California?

The most popular types of Nvidia Engineering jobs in California are:

What job categories do people searching Remote Nvidia Engineering jobs in California look for?

The top searched job categories for Remote Nvidia Engineering jobs in California are:

What cities in California are hiring for Remote Nvidia Engineering jobs?

Cities in California with the most Remote Nvidia Engineering job openings:

Infographic showing various Remote Nvidia Engineering job openings in California as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 100% Remote job distribution.

Senior Applied Research Scientist, Data Curation

Nvidia

Santa Clara, CA • On-site, Remote

Full-time

Posted 6 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 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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA's Curator team is seeking a Senior Applied Research Scientist with experience researching, developing, and deploying deep learning models at scale across a range of modalities. You'll join a team of Applied Research Scientists, Machine Learning and MLOps Engineers working on the next generation of data curation and document extraction pipelines for foundation-model training, including capabilities that power NVIDIA Nemotron Parse, with a focus on structured content extraction, data quality and deduplication at the petabyte-scale. At NVIDIA we're building the foundations upon which modern LLMs are trained. Our work is a critical component in the training of Nemotron LLM models which lead the field of open LLMs. Come be a part of our world-class team building the future of Curation and Retrieval.

What you'll be doing:

  • Working with our team of researchers to develop efficient and performant models and data pipelines that extract and curate multi-modal data (documents, image, audio and videos) used in the training of foundation models.

  • Building pipelines for petabyte-scale extraction and content deduplication, including document and html parsing, fuzzy and near-duplicate deduplication, semantic deduplication, and substring deduplication.

  • Contributing to the expansion and optimization of curation methodologies targeting petabyte-scale multimodal data run across hundred-node GPU clusters to improve the quality of foundation model training sets.

  • Exploring and crafting datasets, metrics, experiments, and validation scripts to develop standard methodologies for research. These methodologies will offer customers clear guidance on which models and pipelines to apply in specific contexts.

  • Helping ML Engineers scale pipelines to production capability through the development of NVIDIA Inference Microservices (NIMs) and blueprints which demonstrate how to deploy NIMs in a pipeline effectively.

  • Writing papers, blog posts, documentation and training materials that help customers understand and take advantage of our research.

  • Keeping up to date with the latest developments in data curation across academia and industry.

What we need to see:

  • Candidates with a Master's, Ph.D. or equivalent experience in data curation, document AI, information retrieval or multimodal research, along with a track record of publication in leading conferences like CVPR, ICCV, ECCV, KDD, etc.

  • Hands-on experience developing computer vision and document-extraction models and pipelines, including layout analysis, OCR, and table, figure, or formula extraction. Kaggle Grandmaster status or a strong record of top-tier results in machine learning competitions is a strong plus.

  • An understanding of the state of the art in data curation research, with a focus on multimodal content extraction and deduplication.

  • 10+ years of experience developing multimodal systems across a range of models and platforms. Information retrieval experience is a big plus.

  • Proven expertise managing distributed data frameworks like Ray, Spark, or Dask, coupled with a history of deploying massive, multi-node machine learning or data processing tasks within production environments.

  • Knowledge of best practices in batching, streaming, and scaling of ingestion pipelines to support real-world applications.

  • Excellent Python programming skills and a strong hands-on experience with PyTorch or comparable modern deep learning frameworks.

  • An ability to share and communicate your ideas clearly through blog posts, papers, kernels, GitHub, etc.

  • Excellent communication and interpersonal skills are required, along with the ability to work in a dynamic, user-focused, distributed team. A history of mentoring junior engineers and interns is a plus.

Location is flexible and the team is remotely situated, focusing on NA/EU time zones. We are looking for candidates in any country where NVIDIA has an office; remote work is accepted.

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 31, 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