Deep Learning Frameworks Intern

We are looking for Deep Learning Frameworks Intern to join the PyTorch team. Join us to design and build the tools used by millions of AI practitioners deploying AI applications scalable to thousands of GPUs.Our team is responsible for the continual delivery of outstanding experience on NVIDIA's hardware with PyTorch. Apply for an opportunity to collaborate with many multi-disciplinary engineering teams within NVIDIA and internationally in the PyTorch open source community to deliver our customers the best of NVIDIA software.What you’ll be doing:As a Deep Learning Frameworks Intern, you will be an integral part of our team, contributing to the advancement of distributed deep learning training workloads through compiler technologies. Your responsibilities will include:Conducting in-depth performance analysis of deep learning workloads, identifying bottlenecks, functional errors, and system inefficiencies.Correlating these performance issues with compiler bugs or missed optimization opportunities and developing strategies to address them.Collaborating with our team to extend existing program transforms or craft new ones based on the recommendations from performance analyses.Staying up-to-date with the latest advancements in deep learning compilers, and proposing innovative solutions to improve the efficiency of deep learning frameworks.Rigorously testing and validating compiler optimizations to ensure the highest quality and performance of model training.What we need to see:Pursuing a Master's, or PhD degree in Computer Science or a related technical field.Proficiency in Python.Experience using machine learning frameworks such as PyTorch or JAX.Some knowledge of compiler concepts such as abstract interpretation, code representations (e.g. SSA form, AST), code generation, and program transformations.Ways to stand out from the crowd:Previous contributions to open-source deep learning compiler projects, such as TVM, or deep learning frameworks.Understanding of the internals of PyTorch and/or JAX.Knowledge of distributed systems, parallel computing, and CUDA programming.NVIDIA is committed to fostering a diverse work environment and is 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.