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
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 some of the affected areas. NVIDIA is building a team to invent the future of foundation models for life sciences and is 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 candidates 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.
- Design experiments to probe the capabilities and limitations of developed foundation models.
- Mentor other 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 via publications, presentations, and research collaborations.
Requirements
- PhD (or equivalent experience) in Computer Science, Computational Biology, or a related field.
- 2+ years of experience 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 languages.
- Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields.
- Experience with areas mentioned in the posting such as genomics, proteomics, molecular dynamics, docking, and protein folding.
Compensation and Benefits
- Base salary ranges provided: 168,000 USD - 264,500 USD for Level 3, and 192,000 USD - 304,750 USD for Level 4.
- Eligible for equity and benefits (link to NVIDIA benefits referenced in the posting).
Additional Information
- Applications for this job will be accepted at least until July 5, 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 an inclusive work environment.