Used Tools & Technologies
LLMRequired Skills & Competences
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.
Python @ 4
Machine Learning @ 4
Mentoring @ 4
Deep Learning @ 4
AI @ 4
- 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 just some of the areas that are affected. NVIDIA is building a 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. This is a hands-on role for someone with deep technical expertise and a passion for advancing the state-of-the-art.
Responsibilities
- 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.
Requirements
- 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.
Compensation and benefits
- Base salary ranges provided by level:
- Level 3: 168,000 USD - 264,500 USD
- Level 4: 192,000 USD - 304,750 USD
- You will also be eligible for equity and benefits.
Additional information
- Applications for this job will be accepted at least until March 8, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.