NVIDIA is using the power of high-performance computing and AI to accelerate digital biology. We are seeking passionate and hardworking individuals to help us realize our mission. As an Applied Deep Learning Scientist, Geometric Deep Learning, you will join a research and development team enthusiastic about infrastructure development and partnerships with industry and academia. This opportunity involves researching, implementing, productizing, and delivering deep learning algorithms for atomistic modeling, life sciences, drug discovery, and materials science. The team carries out applied research and contributes to productizing the results.
What makes this opportunity outstanding is the chance to work at the forefront of AI and computational science, making significant contributions to fields that impact the world. You will be part of an ambitious team driving innovation and pushing the boundaries of what's possible!
What you will be doing:
Develop and refine deep learning algorithms related to geometric deep learning in the biological and materials sciences
Build metrics for and assist with the evaluation of model predictions and results
Stay on top of recent research and discover methods to harness new advancements, either as applied research initiatives or by directly embedding them into product development
Collaborate with multiple AI infrastructure and research teams
Seek opportunities to incorporate advances in the field and other NVIDIA products into our infrastructure
What we need to see:
5+ years of relevant experience
Completed a MS or PhD Degree in a quantitative field such as Statistics, Physics, Computational Biology, Computer Science, Mathematics (or a related field), or equivalent experience
Expertise in deep learning and machine learning
Strong experience with Python for deep learning (PyTorch, Jax, Warp) and relevant specialized deep learning libraries (e.g., PyG, cuEquivariance, e3nn)
Experience with modeling and validation of protein sequences and/or protein structures and related tools
Recognition for technical leadership contributions, capable of self-direction, and willingness to learn from and guide others
Strong communication skills, organized and self-motivated, a phenomenal teammate
Ways to stand out from the crowd:
Knowledge of recent developments in geometric and/or generative deep learning models applied to biological and materials sciences, including AlphaFold3, BioEmu, GNoMe
Background with protein or small molecule or material simulation tools that use atomistic or coarse-grained interaction models such as OpenMM, GROMACS, LAMMPS, TorchSim
Experience with C/C++, CUDA, docker
Experience with open-source development
Relevant publication history and/or conference attendance
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 a diverse 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.NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
