Applied Deep Learning Scientist, Geometric Deep Learning

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 focused on infrastructure development and collaborations with industry and academic partners. This position provides the opportunity to research, implement, productize, and deliver deep learning algorithms for applications to life sciences and drug discovery. The team engages in applied research and then helps productize this work.What you will be doing:Prototype and build deep learning algorithms for graph and geometric deep learning in the biological sciencesDesign metrics for and assist with the evaluation of model predictions and resultsKnow the latest research and identify ways to capitalize on new advancements, either as applied research projects or by directly integrating into product developmentCollaborate with multiple AI infrastructure and research teamsFind opportunities to incorporate advances in the field and other NVIDIA products into our infrastructureWhat we need to see:5+ years of relevant experienceCompleted a MS or PhD Degree in a quantitative field such as Statistics, Physics, Computational Biology, Computer Science, Mathematics (or a related field), or equivalent experienceExpertise in deep learning and machine learningStrong experience with Python for deep learning (PyTorch, TensorFlow, Jax, Warp) and relevant specialized deep learning libraries (e.g. PyG, DGL, e3nn)!Experience with modeling and validation of protein sequences and/or protein structures and related tools, such as biopython, mmseqs2, jackhmmer, PyMolRecognition for technical leadership contributions, capable of self-direction, and willingness to learn from and teach othersYou should display strong communication skills, be organized and self-motivated, and play well with others (be a phenomenal teammate)Ways to stand out from the crowdFamiliarity with latest advances in geometric and/or generative deep learning models in biological sciences, such as AlphaFold and DiffDockExperience with protein or small molecule simulation tools that use atomistic or coarse grained interaction models such as OpenMM and GROMACSExperience with software and tools for modeling and validation of cheminformatics and protein structural data, such as RDKit, Biopython, and PyMolC/C++, CUDA, dockerKnowledge of open source developmentRelevant publication history and/or conference attendanceThe base salary range is $156,000 - $287,500. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits.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.