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 @ 8
CUDA @ 4
Deep Learning @ 4
GenAI
Generative AI @ 8
Parallel Programming @ 4
PyTorch @ 4
Python @ 6
Statistics @ 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
NVIDIA is seeking a generative AI researcher to join the fundamental generative AI research team at NVIDIA Research. The team focuses on advancing generative AI methods for biomolecular design, including small molecules, proteins, and RNA, as well as other scientific applications in GenAI4Science. The role involves fundamental research, novel model development, and collaboration on research that can create real-world impact.
Responsibilities
- Research, design, and implement novel, large-scale generative AI methods.
- Publish original research.
- Collaborate with team members, research teams, and product teams.
- Speak at conferences and events.
- Transfer technology to product groups.
Requirements
- Ph.D. in Computer Science, Engineering, Statistics, or a related field, or equivalent experience.
- At least 2 years of relevant industry or postdoctoral research experience.
- Excellent knowledge of generative AI theory and practice.
- Experience building generative models for molecules, molecular dynamics, proteins, RNA, or other scientific data.
- Excellent programming skills in prototyping environments such as Python.
- Experience with C++ and parallel programming, such as CUDA.
- Knowledge of deep learning frameworks such as PyTorch.
- Outstanding research track record.
- Excellent interpersonal skills.
- Strong mathematical foundation and the ability to analyze and develop novel models.
Benefits
- Equity and benefits are provided.
- NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.
- The application deadline is at least April 6, 2026.
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