Sr. Staff Software Engineer, AI Infra

LinkedIn, the world's largest professional network, is seeking a Sr. Staff Software Engineer to join their AI Infrastructure team. This role presents an exciting opportunity to push the boundaries of scaling large models and shape the future of AI platforms at LinkedIn.

The position focuses on scaling LinkedIn's AI model training, feature engineering, and serving infrastructure handling models with hundreds of billions of parameters. You'll work with cutting-edge technology, optimizing performance across algorithms, AI frameworks, data infrastructure, and hardware to manage thousands of latest GPU cards.

As a technical leader, you'll collaborate with open source communities, working with popular frameworks like TensorFlow, Horovod, Ray, vLLM, and Huggingface. The role involves building next-generation training infrastructure, enabling distributed training for massive models, and developing high-performance serving systems for both LLM and personalization models.

The ideal candidate brings deep expertise in distributed systems, machine learning infrastructure, and technical leadership. You'll tackle challenges at unprecedented scale, handling tens of thousands of QPS, multiple terabytes of data, and billions of model parameters. This role offers the unique opportunity to advance one of the world's most scalable AI platforms while building your career and personal brand in the AI industry.

Working at LinkedIn means joining a culture focused on trust and flexibility, with a hybrid work model that balances remote work with in-office collaboration. The company's vision of creating economic opportunity for every member of the global workforce drives their investment in talent and support for career growth.

This role offers competitive compensation, including a salary range of $180,000 to $300,000, plus annual performance bonus, stock options, and comprehensive benefits. Join LinkedIn to challenge yourself with work that matters while helping shape the future of AI infrastructure at scale.