Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 7
Deep Learning @ 4
LLM
Machine Learning @ 7
Python @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The application of modern AI techniques to drug discovery is radically redefining the field. Genomics, proteomics, molecular dynamics, docking, and protein folding are among the areas being affected. NVIDIA is building a team to develop foundation models for life sciences and is seeking senior research scientists and engineers to advance large-scale foundation models that natively speak the language of cells, biology, and chemistry.
The ideal candidate has a strong background in modern machine learning techniques applied to drug discovery, genomics, proteomics, or medicinal chemistry. This is a hands-on role for someone with deep technical expertise and a passion for advancing the state of the art.
Responsibilities
- Design and train large-scale machine learning models at the intersection of genomics, proteomics, and chemistry.
- Develop experiments to probe the capabilities and limitations of foundation models.
- Mentor team members, lead research initiatives, and help craft strategic roadmaps.
- Work closely with hardware and software teams to improve NVIDIA's platforms for large-scale foundation model applications.
- Engage with the broader research community through publications, presentations, and research collaborations.
Requirements
- PhD or equivalent experience in Computer Science or Computational Biology.
- At least 2 years of experience in deep learning, bioinformatics, chemical engineering, structural biology, or related fields.
- A track record of excellence in engineering and research.
- Deep understanding of modern AI techniques, including deep learning for sequences, diffusion models, large language models, and unsupervised learning.
- Hands-on experience designing, training, and evaluating large neural networks.
- Excellent software engineering and design instincts in Python, C++, or a similar language.
- Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields.
Compensation and Benefits
The base salary is determined based on location, experience, and the pay of employees in similar positions. The base salary ranges are USD 168,000–264,500 for Level 3 and USD 192,000–304,750 for Level 4. The role also includes eligibility for equity and benefits.
Applications will be accepted at least until August 4, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.