Staff Software Engineer, AI Platform

LinkedIn is seeking a Staff Software Engineer to join their AI Platform team, focusing on scaling large model training and serving infrastructure. This is a unique opportunity to work at the intersection of AI and distributed systems at one of the world's largest professional networks.

The role involves pushing the boundaries of scaling AI model training and feature engineering, working with models containing hundreds of billions of parameters. You'll be optimizing performance across algorithms, AI frameworks, data infrastructure, and hardware to maximize the potential of LinkedIn's extensive GPU fleet.

The position is split across several key areas:

1. Model Training Infrastructure: Building next-gen training systems, implementing high-performance data I/O, and working with popular open-source libraries like Huggingface, Horovod, and PyTorch.
2. Feature Engineering: Developing state-of-the-art feature platforms that handle millions of QPS and multi-terabyte datasets.
3. Model Serving Infrastructure: Creating low-latency applications for serving large complex models, including LLMs and personalization models.
4. MLOps: Managing infrastructure for MLOps and experimentation systems across LinkedIn.

This is a hybrid role that can be based in Mountain View, CA, San Francisco, CA, or Bellevue, WA. The position offers competitive compensation and the opportunity to work with talented researchers and engineers while building your career in the AI industry.

The ideal candidate will have significant experience with distributed systems, machine learning infrastructure, and deep learning frameworks. They should be comfortable leading technical initiatives, mentoring other engineers, and contributing to open-source projects.

LinkedIn offers a collaborative environment focused on creating economic opportunity for every member of the global workforce. They value diversity, belonging, and support career growth through meaningful work that matters.