Role at a glance
- Salary
- $168K – $304.8K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 2+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields.
- Education
- PhD (or equivalent experience) in Computer Science or Computational Biology
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Role Summary
NVIDIA is building a team focused on foundation models for life sciences, including applications across genomics, proteomics, molecular dynamics, docking, protein folding, and drug discovery. This role develops large-scale models that work with biological and chemical data and advances their capabilities through research and collaboration.
What You'll Do
- Design and train large-scale machine learning models at the intersection of genomics, proteomics, and chemistry
- Design experiments to probe the capabilities and limitations of developed foundation models
- Mentor team members, lead research initiatives, and help craft strategic roadmaps
- Work with hardware and software teams to improve NVIDIA platforms for large-scale foundation model applications
- Engage with the broader research community through publications, presentations, and research collaborations
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
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 deep learning for sequences, diffusion models, LLMs, and unsupervised learning; hands-on experience designing, training, and evaluating 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.
Required
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
You will also be eligible for equity and benefits.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.