Sr. Staff AI Engineer, AI Modeling Expert

Company Description

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.

Job Description

At LinkedIn, our Core AI (Foundational AI) organization is dedicated to transforming the professional world through innovative solutions, including advanced models, agents, and AI systems. We aim to enhance the experiences of over a billion members worldwide, enabling them to connect, learn, and grow in unprecedented ways. We develop next generation AI technologies that understand the unique needs of professionals and proactively assist them in achieving their goals.

Location:

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This role will be based in Sunnyvale, CA.

Team Overview:

The Data Amplification team's vision is to build the most comprehensive professional identity in the world for LinkedIn members and companies. We combine LinkedIn's rich onsite data with sourced external data, then apply state-of-the-art techniques in large language models, reinforcement learning, and multi-modal inference to create a dynamic, continuously evolving view of the global workforce. This enhanced understanding empowers LinkedIn to deliver more relevant insights, connections, and opportunities, directly advancing our mission to create economic opportunity for every member of the global workforce. We are tackling some of LinkedIn's most challenging modeling problems through unstructured signal inference developing models that extract meaning from noisy, multi-modal professional data using LLMs, embeddings, and advanced entity linking techniques.

Responsibilities:

• Senior Technical Leader who will provide expert-level individual contributions to advanced models, in addition to thought leadership, mentorship, and strategy for a team of 10-15 engineers working on critical high-profile initiatives.
• Continuously improve recommendations and predictions through member feedback loops and RL-driven optimization to build adaptive systems that learn from member interactions.
• This work powers applied AI for member impact: inferring rich, dynamic representations of members and their networks; predicting credibility with high precision; assigning nuanced professional tags at scale for products like ads targeting or recruiter search; and generating high-quality candidate sets for ranking, recommendations, and notifications. These models are deployed end-to-end across LinkedIn's ecosystem, driving smarter feed recommendations, more relevant connection suggestions, and the next generation of semantic search. Our focus is on applied AI at scale, where every improvement directly shapes the professional experience for hundreds of millions of members.
• Lead the development of next-generation inferences, credibility modeling, tagging, and other solutions related to AI-driven personalization.
• Design and train large language models (LLMs), working with model distillation and compression for inference at scale.
• Drive architectural decisions for foundational model development and deployment, ensuring scalability, efficiency, and robustness.
• Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation and excellence.
• Stay at the forefront of research in AI modeling and related fields, contributing to the broader research community through publications and presentations.
• Define and execute rigorous evaluation strategies to benchmark the performance of foundational models against state-of-the-art solutions.

Qualifications

Basic Qualifications:

• 2+ years as a Technical Lead, Staff Engineer, Principal Engineer, or equivalent.
• 5+ years of industry experience in AI or Machine Learning Engineering.
• BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience

Preferred Qualifications:

• 10+ years of overall industry/research experience in AI and/or Machine Learning.
• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field Expert-level understanding of deep learnin