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What is an Nvidia Research job?

An Nvidia Research job involves conducting cutting-edge research in areas like artificial intelligence, computer graphics, and high-performance computing. Researchers work on innovative projects that push the boundaries of technology, often collaborating with academia and industry partners. These roles typically require expertise in machine learning, deep learning, hardware acceleration, or related fields. Team members publish papers, develop prototypes, and contribute to Nvidia's long-term technological advancements.

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

Excelling in Nvidia Research typically requires a PhD or advanced degree in computer science, electrical engineering, or a related field, with strong expertise in machine learning, computer vision, and deep learning algorithms. Familiarity with programming languages such as Python and C++, and experience using frameworks like TensorFlow or PyTorch, as well as CUDA for GPU computing, are also important. Excellent problem-solving abilities, creativity, and effective collaboration and communication skills help set candidates apart. These skills are crucial for conducting innovative research, collaborating with multidisciplinary teams, and advancing the field of AI and graphics technology.

What opportunities for career growth and advancement are available within Nvidia Research?

Nvidia Research offers a dynamic environment where researchers can grow by taking on increasingly complex projects, publishing groundbreaking work, and collaborating with world-class experts. Many team members advance to senior and principal researcher roles or transition into leadership positions overseeing multi-disciplinary research initiatives. Nvidia also encourages continuous learning through conferences, workshops, and internal seminars, which further support professional development. As the company continues to expand its research footprint, there are ample opportunities to shape new areas of innovation and make a lasting impact on both the organization and the industry.

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Nvidia Research jobs near you
Infographic showing various Nvidia Research job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 45% As Needed, 47% Full Time, 6% Nights, and 1% Summer. Highlights an 85% Physical, 7% Hybrid, and 8% Remote job distribution.
Lead Engineer, Healthcare Data Operations and Strategy

Lead Engineer, Healthcare Data Operations and Strategy

Nvidia

Santa Clara, CA • On-site

$120K - $158K/yr

Full-time

Re-posted 7 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

At NVIDIA, we're building the platforms to accelerate the healthcare applications of tomorrow. Software, Hardware, as well as data. We're looking for dedicated contributors who know how to focus on the latter. This is an opportunity to influence the direction of NVIDIA research, engineering, and ultimately the products which our customers build.

This role leads healthcare data operations and guides its strategy. You decide what to build next and collaborate with community partners to build it. You also establish the MLOps backbone that makes each program a durable, growing asset. You connect leading clinicians, academic researchers, medtech industry partners, and NVIDIA's engineering and product teams.

What You'll Be Doing:

  • Define a portfolio strategy and selection methodology for NVIDIA's healthcare data programs with key collaborators. Prioritize modalities, clinical domains, and partner cohorts based on scientific and market impact, downstream model value, partner readiness, and technical feasibility.

  • Drive the tactical execution of new healthcare data collaborations end-to-end: prioritizing, data contribution agreements and licensing, contribution standards, release planning, and public launch.

  • Architect and build our healthcare data MLOps platform that ingests, curates, validates, governs, and serves multi-institution healthcare data at scale. Combine NVIDIA's internal tooling with outstanding external systems when appropriate.

  • Partner directly with NVIDIA healthcare and model training teams (e.g., GR00T, Cosmos) to ensure data programs are sequenced and crafted to feed the highest-priority needs.

  • Establish data quality, provenance, de-identification, and governance standards that scale across modalities and meet the regulatory and compliance expectations of global clinical partners.

What We Need to See:

  • 12+ years working with healthcare data - building datasets, running data programs, or leading MLOps workflows in a healthcare or medtech setting.

  • Strong technical proficiency across the healthcare data lifecycle: ingestion, curation, annotation, de-identification, governance (HIPAA, GDPR, IRB workflows), and serving for training and evaluation.

  • Hands-on experience with MLOps tooling - data lakes/lakehouses, dataset versioning (e.g., Hugging Face Datasets, LakeFS, DVC), workflow orchestration, validation frameworks - and a clear point of view on when to build versus integrate.

  • Familiarity operating at the intersection of strategy, partnerships, and engineering - able to set portfolio direction one day and review schema choices or pipeline architectures the next.

  • BS or higher in Computer Science, Biomedical Engineering, Computational Biology, or a related technical field, or equivalent experience.

Ways to Stand Out from the Crowd:

  • Direct healthcare industry experience - including familiarity with how device data is generated, retained, and released.

  • Track record of launching publicly released, commercially usable healthcare datasets.

  • Experience standing up data infrastructure for foundation model training, including multi-modal sensor data.

  • Deep relationships across the global clinical AI community (MedTech or biopharma), and a history of converting those relationships into shipped artifacts.

  • Familiarity with NVIDIA platforms relevant to healthcare AI - Holoscan, BioNeMo, Cosmos, Isaac, NeMo Data Designer, or Omniverse.

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 for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 12, 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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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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