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.