Senior Software Engineer, AI Platform

LinkedIn, the world's largest professional network, is seeking a Senior Software Engineer to join their AI Platform team. This role offers an exciting opportunity to work on cutting-edge AI infrastructure that powers LinkedIn's machine learning capabilities across recommendation systems, large language models, and computer vision applications.

The position focuses on scaling LinkedIn's AI model training, feature engineering, and serving infrastructure to handle models with hundreds of billions of parameters. You'll work with state-of-the-art technologies and contribute to open-source projects, collaborating with teams that include many open source committers to projects like TensorFlow, Horovod, Ray, vLLM, and DeepSpeed.

As a Senior Engineer, you'll be responsible for building high-performance training infrastructure, optimizing data I/O, enabling distributed training at massive scale, and developing containerized pipeline orchestration systems. The role involves working with cutting-edge AI frameworks and technologies while solving complex challenges in areas like model parallelism, tensor parallelism, and feature engineering at scale.

The position offers a competitive salary range of $128,000 - $210,000, along with comprehensive benefits including equity, health coverage, and flexible work arrangements. The hybrid work model allows for both remote work and in-office collaboration at LinkedIn's locations in Mountain View, San Francisco, or Bellevue.

This is an excellent opportunity for experienced engineers passionate about AI infrastructure to make a significant impact on technology that serves hundreds of millions of professionals worldwide. You'll work in an inclusive environment that values diversity and provides strong support for career growth and professional development.

The ideal candidate will have experience with distributed systems, deep learning frameworks, and a track record of building scalable infrastructure. You'll be joining a team that not only builds essential infrastructure but also actively contributes to the broader AI community through open-source contributions and technological innovations.