Software Engineer - AI Platform

LinkedIn is seeking a Software Engineer to join our AI Platform team, focusing on pushing the boundaries of scaling large models and AI infrastructure. This role offers a unique opportunity to work on cutting-edge AI technologies while contributing to the world's largest professional network.

The position involves working with state-of-the-art AI infrastructure, handling models with hundreds of billions of parameters, and optimizing performance across various layers of the stack. You'll be part of a team that manages thousands of latest GPU cards and collaborates closely with the open source community, including projects like TensorFlow, Horovod, Ray, vLLM, and Huggingface.

Key responsibilities include building next-gen training infrastructure, optimizing data I/O, enabling distributed training for large-scale models, and developing containerized pipeline orchestration systems. You'll work on feature engineering platforms that handle millions of QPS and multi-terabytes of data, while also contributing to low-latency serving infrastructure for complex AI models.

The ideal candidate should have experience in deep learning systems, distributed computing, and programming languages like Python, Java, or C++. You'll be working in a hybrid environment, combining remote work with office presence in either Mountain View, San Francisco, or Bellevue.

This role offers competitive compensation ($107,000-$176,000), comprehensive benefits, and the opportunity to work with leading experts in AI and machine learning. You'll be part of LinkedIn's mission to create economic opportunity for every member of the global workforce while working on some of the most challenging problems in AI infrastructure.

Join us to challenge yourself with work that matters, contribute to open-source projects, and help shape the future of AI at scale. The role provides excellent growth opportunities, working with cutting-edge technologies and a talented team of researchers and engineers who are pushing the boundaries of what's possible in AI.