Data Contributor Jobs at NVIDIA with Visa Sponsorship
Data Contributor roles at NVIDIA sit at the intersection of large-scale data pipelines and AI infrastructure, requiring sharp technical instincts and domain fluency. NVIDIA has a consistent track record of sponsoring international talent across multiple visa categories for this function, making it a realistic target for qualified applicants.
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Get Access To All JobsWould you enjoy researching new algorithms and memory management techniques to accelerate databases on modern computer architectures? Do you like investigating hardware and system bottlenecks, and optimizing performance of data intensive applications? Are you excited about the opportunity to work on the top tier edge of technology with both visibility and impact to the success of a leader like NVIDIA? If so, the Solution Architecture Team invites you to consider this opportunity.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Join our team with varied strengths today!
What you will be doing:
- In this role, you will research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications.
- Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex data intensive workloads to ensure the best possible performance of current GPU architectures.
- Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.
- Influence partners (industry and academia) to push the bounds of data processing with NVIDIA’s full product line.
What we need to see:
- Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent experience.
- Programming fluency in C/C++ with a deep understanding of algorithms and software design.
- Hands-on experience with low-level parallel programming, e.g. CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.
- In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
- Domain expertise in high performance databases, ETL, data analytics and/or vector database.
- Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.
Ways to stand out from the crowd:
- Experience optimizing/implementing database operators or query planner, especially for parallel or distributed frameworks (e.g. production database or Spark).
- Background in optimizing vector database index build and/or search.
- Experience profiling and optimizing CUDA kernels.
- Background with compression, storage systems, networking, and distributed computer architectures.
Data Analytics is one of the rapidly growing fields in GPU accelerated computing. Data preprocessing and data engineering are traditionally CPU based and are becoming the bottleneck for Machine Learning (ML) and Deep Learning (DL) applications, as performance of the frameworks and core ML/DL libraries has been highly optimized leveraging GPUs. Many of today’s applications have complex data analytics pipelines that can benefit from optimizations in memory management, compression, parallel algorithms like sort, search, join, aggregation, groupby, scaling up to multi GPU systems, and scaling out to many nodes. Take a look at some of the open-source projects that NVIDIA employees have worked on: RAPIDS cuDF, NVIDIA nvcomp, NVIDIA Distributed join, NVIDIA cuCollections. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, 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 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
Would you enjoy researching new algorithms and memory management techniques to accelerate databases on modern computer architectures? Do you like investigating hardware and system bottlenecks, and optimizing performance of data intensive applications? Are you excited about the opportunity to work on the top tier edge of technology with both visibility and impact to the success of a leader like NVIDIA? If so, the Solution Architecture Team invites you to consider this opportunity.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Join our team with varied strengths today!
What you will be doing:
- In this role, you will research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications.
- Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex data intensive workloads to ensure the best possible performance of current GPU architectures.
- Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.
- Influence partners (industry and academia) to push the bounds of data processing with NVIDIA’s full product line.
What we need to see:
- Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent experience.
- Programming fluency in C/C++ with a deep understanding of algorithms and software design.
- Hands-on experience with low-level parallel programming, e.g. CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.
- In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
- Domain expertise in high performance databases, ETL, data analytics and/or vector database.
- Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.
Ways to stand out from the crowd:
- Experience optimizing/implementing database operators or query planner, especially for parallel or distributed frameworks (e.g. production database or Spark).
- Background in optimizing vector database index build and/or search.
- Experience profiling and optimizing CUDA kernels.
- Background with compression, storage systems, networking, and distributed computer architectures.
Data Analytics is one of the rapidly growing fields in GPU accelerated computing. Data preprocessing and data engineering are traditionally CPU based and are becoming the bottleneck for Machine Learning (ML) and Deep Learning (DL) applications, as performance of the frameworks and core ML/DL libraries has been highly optimized leveraging GPUs. Many of today’s applications have complex data analytics pipelines that can benefit from optimizations in memory management, compression, parallel algorithms like sort, search, join, aggregation, groupby, scaling up to multi GPU systems, and scaling out to many nodes. Take a look at some of the open-source projects that NVIDIA employees have worked on: RAPIDS cuDF, NVIDIA nvcomp, NVIDIA Distributed join, NVIDIA cuCollections. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, 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 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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Get Access To All JobsTips for Finding Data Contributor Jobs at NVIDIA Jobs
Align your portfolio to NVIDIA's data scale
NVIDIA's Data Contributor roles emphasize experience with high-volume, structured and unstructured datasets used in AI training pipelines. Before applying, document projects where you managed, labeled, or validated data at scale, with clear output metrics that reflect production-level work.
Target roles with specialty occupation language
H-1B eligibility depends on the role qualifying as a specialty occupation under USCIS standards. Look for NVIDIA Data Contributor postings that explicitly require a bachelor's degree or higher in a specific field like computer science, statistics, or data engineering, not just preferred qualifications.
Check E-3 eligibility before the H-1B lottery
If you hold Australian citizenship, NVIDIA's E-3 sponsorship history for this function means you can pursue a visa outside the annual H-1B cap and lottery. E-3 applications can be filed at a U.S. consulate in Australia with a certified Labor Condition Application from your employer.
Understand NVIDIA's internal transfer and team structure
Data Contributor openings at NVIDIA often sit within specific product or research divisions. Identifying which team is hiring, whether it is the data platform group or an AI content team, helps you tailor your application and ask informed sponsorship questions during recruiter screens.
Prepare your credentials before the offer stage
NVIDIA's H-1B and EB-2 filings both require documentation of your educational background and work history. Get your foreign degree evaluated by a NACES-accredited service early so you are not delaying the I-129 or PERM process after an offer is extended.
Use Migrate Mate to filter open roles by sponsorship type
Finding Data Contributor positions at NVIDIA that align with your visa category takes more than a generic job search. Migrate Mate lets you filter NVIDIA's open roles by the specific visa types sponsored, so you can focus applications on positions where your status is a realistic fit.
Data Contributor at NVIDIA jobs are hiring across the US. Find yours.
Find Data Contributor at NVIDIA JobsFrequently Asked Questions
Does NVIDIA sponsor H-1B visas for Data Contributors?
Yes, NVIDIA sponsors H-1B visas for Data Contributor roles. The role must qualify as a specialty occupation under USCIS guidelines, meaning it requires at least a bachelor's degree in a directly related field. NVIDIA has a well-established sponsorship process, and their recruiting team is generally familiar with the H-1B petition timeline, including premium processing options if your start date requires expedited adjudication.
Which visa types are commonly used for Data Contributor roles at NVIDIA?
H-1B is the most common nonimmigrant visa for Data Contributor positions at NVIDIA, but the company also sponsors E-3 visas for Australian citizens and pursues EB-2 and EB-3 immigrant visa pathways for employees seeking permanent residence. The right visa depends on your nationality, degree, and how the specific role is classified. Roles requiring specialized data expertise in AI or machine learning pipelines tend to support stronger petition arguments.
What qualifications or experience are expected for Data Contributor roles at NVIDIA?
NVIDIA typically looks for candidates with a bachelor's or master's degree in computer science, data science, linguistics, or a related field, depending on the team. Hands-on experience with data annotation, curation, or pipeline work on AI or ML projects is valued. For visa sponsorship purposes, the degree field matters, since USCIS evaluates whether your education directly corresponds to the duties of the role.
How do I apply for Data Contributor jobs at NVIDIA?
You can browse and apply for Data Contributor roles at NVIDIA directly through their careers portal, or use Migrate Mate to filter open positions by visa sponsorship type so you only see roles where your immigration status is a fit. When applying, tailor your resume to reflect data pipeline experience relevant to NVIDIA's AI and product teams. Mention your visa status early in recruiter conversations to avoid surprises later in the process.
How do I understand the sponsorship timeline for a Data Contributor role at NVIDIA?
For H-1B sponsorship, NVIDIA would file a Labor Condition Application with the DOL before submitting the I-129 petition to USCIS. Standard adjudication takes three to six months, while premium processing can return a decision in roughly two weeks. If you are already in the U.S. on a valid status, NVIDIA can file a change of status concurrently. For E-3 applicants, the process moves faster since it does not require a USCIS petition and can be handled at a consulate.
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