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, handling models with hundreds of billions of parameters and large-scale feature engineering for all AI use cases. You'll be working with state-of-the-art technology and contributing to open-source projects, as the team includes many open source committers to projects like TensorFlow, Horovod, Ray, vLLM, and Huggingface.
As a Senior Software Engineer, you'll be responsible for building next-generation training infrastructure, optimizing performance across algorithms, AI frameworks, and hardware, and working with LinkedIn's extensive GPU fleet. The role involves both technical leadership and hands-on development, requiring expertise in distributed systems, machine learning infrastructure, and high-performance computing.
The position offers competitive compensation ($128,000 - $210,000), comprehensive benefits, and the opportunity to work in a hybrid environment from either Mountain View, San Francisco, or Bellevue offices. LinkedIn's culture emphasizes belonging, career growth, and work-life balance, making it an ideal place for talented engineers who want to make an impact on global professional networking while advancing their careers.
Key responsibilities include designing high-performance data I/O systems, enabling distributed training for massive models, optimizing deep learning frameworks, and mentoring other engineers. The role requires collaboration with open-source communities and internal teams to build scalable solutions for LinkedIn's growing AI needs.
This is an excellent opportunity for experienced engineers passionate about AI infrastructure who want to work at scale, contribute to open-source projects, and help shape the future of professional networking through advanced machine learning capabilities.