Senior Applied Research Scientist

NVIDIA
Location
Santa Clara, CA
Job Type
Full-time
Posted
May 19, 2026
Views
86

Job Description

The application of modern AI techniques to drug discovery, is radically redefining the field. Genomics, proteomics, molecular dynamics, docking, and protein folding are just some of the areas that are affected. NVIDIA is building an outstanding team to invent the future of foundation models for life sciences.  We are seeking senior research scientists and engineers to push the frontier of large-scale foundation models that natively speak the language of cells, biology, and chemistry.  The ideal candidate has a strong background in the combination of modern machine learning techniques as applied to drug discovery, genomics, proteomics, or medical chemistry.  This is a hands-on role for someone with deep technical expertise and a passion for advancing the state-of-the-art.

What you’ll be doing

Designing and training large-scale machine learning models at the intersection of genomics, proteomics, and chemistry

Experimental design for probing the capabilities and limitations of the foundation models that are developed

Mentoring other team members, leading research initiatives, and helping to craft strategic roadmaps

Working closely with hardware and software teams to improve NVIDIA’s platforms for large-scale foundation model applications

Engaging with the broader research community via publications, presentations, and research collaborations

What we need to see

PhD (or equivalent experience) in Computer Science or Computational Biology

2+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields.

Track record of excellence in engineering and research

Deep understanding of modern AI techniques: deep learning for sequences, diffusion models, LLMs, unsupervised learning. Hands-on practical know-how of how to design, train, and evaluate large neural networks.

Excellent software engineering and design instincts in Python, C++, or similar.

Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields

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 May 22, 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.

Frequently Asked Questions

Where is this Senior Applied Research Scientist position located?
This role is located in Santa Clara, CA.
What are the main responsibilities for this role?
You'll be designing and training large-scale machine learning models, designing experiments, mentoring team members, working with hardware/software teams, and engaging with the research community.
What qualifications are required for this position?
A PhD (or equivalent experience) in Computer Science or Computational Biology and 2+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields are required.
What is the salary range for this position?
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.
When does the application period end?
Applications for this job will be accepted at least until May 22, 2026.

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Job Information

Source: manual
AI Relevance: 85/100 (Highly relevant)
Remote Type: onsite
Experience: Mid
Allowed Locations: Worldwide
Skills & Tags:
AI machine learning deep learning LLM foundation models bioinformatics computational biology drug discovery genomics proteomics

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