Staff Software Engineer, AI Platform

LinkedIn is seeking a Staff Software Engineer to join their AI Platform team, focusing on pushing the boundaries of scaling large models. This role presents an exciting opportunity to work at the intersection of AI infrastructure and distributed systems at one of the world's largest professional networks.

The position involves working with cutting-edge AI technologies, including large language models, recommendation systems, and computer vision models. You'll be responsible for scaling LinkedIn's AI model training and feature engineering infrastructure, handling models with hundreds of billions of parameters. The team operates a substantial GPU fleet with thousands of latest-generation cards and works closely with the open source community.

Key areas of focus include:

1. Model Training Infrastructure: You'll build next-gen training infrastructure for AI use cases, optimize data I/O, work with popular libraries like Huggingface and PyTorch, and enable distributed training for massive models.

2. Feature Engineering: You'll work on the state-of-the-art Feature Platform, handling millions of QPS and multi-terabyte datasets, using technologies like Spark, Beam, and Flink.

3. Model Serving Infrastructure: You'll develop low-latency applications serving large complex models, focusing on compute efficiency and GPU-based inference at scale.

4. MLOps: You'll contribute to systems handling AI metadata, observability, orchestration, and experimentation.

The role offers the opportunity to influence the direction of AI infrastructure at LinkedIn while working with a talented team of researchers and engineers. You'll have the chance to build your career and personal brand in the AI industry while solving challenging problems at scale.

The position is hybrid, combining remote work with office presence in either Mountain View, San Francisco, or Bellevue. LinkedIn offers a collaborative environment where you can make a significant impact on the future of AI infrastructure while working with cutting-edge technologies and contributing to the open source community.

This is an excellent opportunity for experienced engineers passionate about AI infrastructure, distributed systems, and building scalable solutions that power LinkedIn's AI capabilities across recommendation systems, language models, and computer vision applications.