"pytorch distributed" Jobs
71 open tech roles matching “pytorch distributed”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: PyTorch, Python, Kubernetes. Every listing is re-checked daily and closed roles are removed.
Showing 20 of 71 results
Join Perplexity AI as a Technical Staff member to enhance our AI inference engine with cutting-edge technologies.
Join Perplexity AI as an AI Infrastructure Engineer to design and optimize large-scale AI training and inference clusters.
Join Baseten as a Post-Training Research Engineer to build in-house tooling for efficient and high-quality machine learning models.
Join Databricks as a Staff Software Engineer to drive the architecture of a managed GPU training platform for large-scale AI models.
Join Databricks as a Senior Software Engineer to build and scale a managed GPU training platform for AI models.
Lead a high-performing engineering team at Databricks to enhance the AI Runtime product for GPU training infrastructure.
Join Databricks as a Staff Software Engineer to build LLM infrastructure for large-scale AI inference workloads.
Join Databricks as a Senior Software Engineer to build infrastructure for AI applications and improve distributed AI workloads.
Drive technical direction for training infrastructure and operations within Pegasus at a growing AI company focused on video understanding.
Join Inferact as a co-op student to work on cutting-edge AI inference systems in a hands-on engineering role.
Join Hedra as a Research Engineer to lead the development of action-conditioned world models in a pioneering Physical AI team.
Join Preference Model as a Research Engineer to advance self-directed learning in large language models within a fast-paced startup.
Lead a multidisciplinary research team to advance large-scale machine learning efficiency at Databricks.
Drive research on Pegasus's complex problems in a hybrid role at a growing AI company focused on video understanding.
Join Reflection AI as a Member of Technical Staff to research and build solutions for large language models in a fast-paced startup environment.