AI Engineering Manager, Knowledge Extraction & Linking

$200,000 - $268,000/Yr

LinkedIn - Mountain View, CA

Full-time - Mid Level

Remote - Mountain View, CA

5,001-10,000 employees

About the position

The AI Engineering Manager for Knowledge Extraction & Linking at LinkedIn will lead a team focused on developing advanced AI solutions that enhance semantic understanding and knowledge graph capabilities. This role is pivotal in shaping the future of professional knowledge systems, impacting millions of professionals globally by improving how they discover opportunities and connect with others. The manager will oversee the integration of large language models with knowledge graph technologies, driving innovation and collaboration across various teams.

Responsibilities

• Lead and mentor a team of ML engineers and researchers in developing LLM and knowledge graph solutions.
• Drive technical strategy for integrating large language models with knowledge graph technologies.
• Participate in key technical and design discussions with technical leads across multiple projects.
• Collaborate with application engineering, product, and partner teams to design scalable machine learning solutions.
• Implement and maintain best engineering and scientific practices to ensure team productivity.
• Drive faster iterations via A/B experiments and data-driven decision making.
• Attract and retain world-class talent while providing technical guidance and career development.

Requirements

• 5+ years of professional experience in AI algorithms, Machine Learning, LLMs, or related engineering disciplines.
• 1+ year(s) of experience in a Manager role.
• Bachelor's degree in Computer Science or related technical field or equivalent technical experience.

Nice-to-haves

• 2+ years of experience as an Engineering Manager or TLM, leading AI engineering or research teams.
• 7+ years of total professional experience in AI, Machine Learning, or related areas.
• MS or PhD in Computer Science, Machine Learning, Statistics, or related fields.
• Experience with knowledge graphs and entity linking systems.
• Deep understanding of modern ML frameworks and large-scale AI systems.
• Experience with attention-based models and embedding techniques.
• Proficiency in knowledge graph technologies and entity resolution.
• Strong background in MLOps and experimentation frameworks.
• Expertise in Python, Java, and distributed computing systems.

Benefits

• Generous health and wellness programs
• Time away for employees of all levels
• Annual performance bonus
• Stock options
• Comprehensive benefits package