Job description

For decades, NVIDIA has been at the forefront of accelerated computing, driving innovation in fields ranging from computer graphics to artificial intelligence. Today, we're leveraging this legacy to revolutionize digital biology and to accelerate drug discovery. Our cutting-edge GPU technology serves as the computational engine for groundbreaking research, enabling scientists to model complex biological systems, analyze and harmonize massive datasets, and accelerate the drug discovery process. We're looking for a Research Scientist who shares our vision for transforming healthcare. This is a unique opportunity to apply your expertise in a fast-paced, collaborative environment where you'll be instrumental in developing the tools that will redefine what is possible in drug discovery, virtual cell, and beyond. As part of our team, you'll work alongside other researchers, developers, and experts in the field to tackle some of the most challenging and impactful problems of our time. What you'll be doing: • Building models and datasets that connect early drug discovery to the clinic, spanning drug perturbation prediction, clinical translatability, patient stratification, and digital twins. • Designing benchmarks and evaluation methods for agentic systems in this domain, and characterizing where current LLMs underperform. • Publishing original research and releasing open-source software. • Collaborating with external research leaders in digital biology. • Partnering with research and engineering teams across NVIDIA to move research into products and services. What we need to see: • Bs/Ms Or PhD in a quantitative field: computational biology, computer science, computational chemistry, physics, mathematics, or equivalent experience. • Publication record in digital biology, ideally with clinical applications. • 5 plus years of experience building and training machine learning models at scale, along with the compute infrastructure that supports them. • Proficiency with modern ML frameworks such as PyTorch or JAX. • Fluency with the statistical foundations this work rests on (causal inference, experimental design, or clinical biostatistics). • Ability to learn from and teach others to keep up to speed on the latest developments and tools in the field. • Ability to work together in a tight-knit team environment. Ways to stand out from the crowd: • Track record of state-of-the-art methods development in the clinical domain. • Experience with clinical trial data, electronic health records, or regulatory science. • Rigor in evaluation: temporal validation, benchmark design, assessing data leakage and easy inference, characterizing distribution shift. • Background in open-source development. 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 168,000 USD - 264,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 8, 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.

Requirements

Must-haves

Building models and datasets that connect early drug discovery to the clinic, spanning drug perturbation prediction, clinical translatability, patient stratification, and digital twins.
Designing benchmarks and evaluation methods for agentic systems in this domain, and characterizing where current LLMs underperform.
Publishing original research and releasing open-source software.
Collaborating with external research leaders in digital biology.
Partnering with research and engineering teams across NVIDIA to move research into products and services.
Bs/Ms Or PhD in a quantitative field: computational biology, computer science, computational chemistry, physics, mathematics, or equivalent experience.
Publication record in digital biology, ideally with clinical applications.
5 plus years of experience building and training machine learning models at scale, along with the compute infrastructure that supports them.
Proficiency with modern ML frameworks such as PyTorch or JAX.
Fluency with the statistical foundations this work rests on (causal inference, experimental design, or clinical biostatistics).
Ability to learn from and teach others to keep up to speed on the latest developments and tools in the field.
Ability to work together in a tight-knit team environment.
Track record of state-of-the-art methods development in the clinical domain.
Experience with clinical trial data, electronic health records, or regulatory science.
Rigor in evaluation: temporal validation, benchmark design, assessing data leakage and easy inference, characterizing distribution shift.
Background in open-source development.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 8, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningmlai

Platform: eightfold
Effort: medium

Benefits

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Vision