Senior Applied Research Scientist, Multimodal Foundation Models – Healthcare

$184K - $356K Santa Clara, CA, US Senior Research Scientist

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Skills & Technologies

Pytorch

About This Role

AI job market dashboard showing open roles by category

NVIDIA is redefining healthcare through accelerated computing and AI. We are seeking passionate researchers to advance longitudinal multimodal foundation models for healthcare. Recent progress in medical AI has improved the interpretation of individual images and clinical records, but many significant healthcare decisions depend on understanding how a patient’s condition changes over time. This role will explore models that learn from longitudinal medical imaging, electronic health records, laboratory measurements, genomics, medications, diagnoses, and clinical outcomes. The research will support applications such as disease progression modeling, treatment response prediction, and precision medicine.

You will join an applied research team that develops medical AI algorithms, foundation models, datasets, and workflows. Our work combines publication\-quality research with practical implementation and open\-source contributions. You will collaborate with researchers, engineers, healthcare organizations, and industry partners to evaluate new ideas and translate successful research into software, models, and workflows that can be used by the broader healthcare ecosystem.

What you will be doing:

  • Conduct research on longitudinal multimodal foundation models that learn from heterogeneous healthcare data, including medical imaging, electronic health records (EHR), laboratory measurements, genomics, medications, diagnoses, and clinical outcomes.
  • Develop novel foundation model architectures and training strategies for disease progression modeling, treatment response prediction, temporal reasoning, and multimodal generative modeling.
  • Build large\-scale datasets, benchmarks, and open\-source foundation models that advance the state of the art in healthcare AI.
  • Collaborate with researchers across Healthcare AI, BioNeMo, and other NVIDIA teams to develop multimodal biological foundation models spanning imaging and molecular data.
  • Partner with leading healthcare institutions, medical device companies, pharmaceutical companies, and academic collaborators to translate cutting\-edge research into impactful healthcare AI solutions.
  • Publish research in leading AI and healthcare venues, contribute to open\-source software and models, and help define the future direction of healthcare foundation models.

What we need to see:

  • PhD in Computer Science, Machine Learning, Biomedical Engineering, Computational Biology, Electrical Engineering, or a related quantitative field (or equivalent experience).
  • 8\+ years of relevant industry experience focusing on medical AI research.
  • Research experience developing multimodal foundation models that integrate heterogeneous clinical or biological data, such as medical imaging, electronic health records (EHR), laboratory measurements, genomics, pathology, medications, diagnoses, and clinical outcomes, with an emphasis on longitudinal modeling, temporal reasoning, or disease progression prediction.
  • Experience developing and training large\-scale foundation models using modern deep learning frameworks such as PyTorch.
  • Experience using AI coding assistants and agentic AI workflows to accelerate software development, experimentation, and research productivity.
  • Strong software engineering and experimental skills, including building scalable, reproducible research pipelines.
  • Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary research and engineering teams.

Ways to stand out from the crowd:

  • Experience developing foundation models that bridge medical imaging with molecular or biological data, such as genomics, transcriptomics, proteomics, or spatial omics.
  • A demonstrated record of impactful research in multimodal AI, foundation models, or deep learning, including publications at leading conferences or journals (e.g., NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, ACL, MICCAI, Nature, Science, or equivalent venues).
  • Experience scaling foundation models using distributed GPU training and high\-performance computing.
  • Experience collaborating with healthcare providers, pharmaceutical companies, medical device companies, or academic medical centers to translate research into real\-world healthcare applications.
  • Background with NVIDIA's GPU and AI technologies, such as CUDA, cuDNN, and TensorRT.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward\-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard\-working and talented people in the world working for us. If you're creative and passionate about developing cloud services 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 184,000 USD \- 287,500 USD for Level 4, and 224,000 USD \- 356,500 USD for Level 5\.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 17, 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.

Salary Context

This $184K-$356K range is above the 75th percentile for Research Scientist roles in our dataset (median: $195K across 149 roles with salary data).

Role Details

Company NVIDIA
Title Senior Applied Research Scientist, Multimodal Foundation Models – Healthcare
Location Santa Clara, CA, US
Category Research Scientist
Experience Senior
Salary $184K - $356K
Remote No

About This Role

Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.

The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.

Across the 4,317 AI roles we're tracking, Research Scientist positions make up 4% of the market. At NVIDIA, this role fits into their broader AI and engineering organization.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

What the Work Looks Like

A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

Skills Required

Pytorch (15% of roles)

PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.

Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.

Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

Compensation Benchmarks

Research Scientist roles pay a median of $222,200 based on 378 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($270K) sits 22% above the category median. Disclosed range: $184K to $356K.

Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.

NVIDIA AI Hiring

NVIDIA has 28 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Product Manager, Research Scientist. Positions span Santa Clara, CA, US, Austin, TX, US, CA, US. Compensation range: $195K - $431K.

Location Context

Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).

Career Path

Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.

From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.

The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.

What to Expect in Interviews

Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.

When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

AI Hiring Overview

The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.

The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

The AI Job Market Today

The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 378 roles with disclosed compensation, the median salary for Research Scientist positions is $222,200. Actual compensation varies by seniority, location, and company stage.
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
NVIDIA is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Research Scientist positions include Research Lead, Distinguished Scientist, VP of Research. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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