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 is a unique opportunity to work at the intersection of AI infrastructure and distributed systems at one of the world's largest professional networks.

The role spans three critical areas: Model Training Infrastructure, Feature Engineering, and Model Serving Infrastructure. You'll be working with cutting-edge technologies to scale LinkedIn's AI capabilities, handling models with hundreds of billions of parameters and managing feature engineering infrastructure for diverse AI use cases from recommendation systems to computer vision.

As a Staff Engineer, you'll be responsible for optimizing performance across algorithms, AI frameworks, data infrastructure, and hardware, particularly focusing on GPU fleet optimization. The team has strong ties to the open source community, with many team members being active contributors to projects like TensorFlow, Horovod, Ray, vLLM, and DeepSpeed.

The position offers the opportunity to work on challenging technical problems at scale, including:

• Building next-generation training infrastructure for AI use cases
• Developing high-performance data I/O systems
• Implementing distributed training for massive models
• Creating feature engineering platforms that handle millions of QPS
• Designing low-latency serving systems for complex models

The role combines technical leadership with hands-on development, requiring both deep technical expertise and strong collaborative skills. You'll work in a hybrid environment, splitting time between remote work and office presence in either Mountain View, San Francisco, or Bellevue.

LinkedIn offers competitive compensation, comprehensive benefits, and the chance to impact how millions of professionals connect and advance their careers. The company's culture emphasizes trust, flexibility, and professional growth, making it an ideal environment for experienced engineers looking to make a significant impact in the AI infrastructure space.