Applied Deep Learning Scientist, Geometric Deep Learning

Details

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!

Responsibilities

• 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

Requirements

• 5+ years of relevant experience
• Completed an 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

Compensation & Benefits

• Base salary ranges (determined based on location, experience, and comparable employees):
  • 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 (see NVIDIA benefits page).

Additional information

• Applications for this job will be accepted at least until January 16, 2026.
• 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 is an equal opportunity employer. They do not discriminate 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.