Senior AI Engineering Manager, Talent Marketplace AI

• Full-time
• Workplace Type:
  Hybrid

Linked In is the world’s 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. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Team Overview: Creating economic opportunity for every member of the global workforce is Linked In’s core mission. At Talent Marketplace Matching team, we tackle foundational challenges that enable Linked In’s Talent Solutions ecosystem to fully harness the power of our rich and diverse talent data.

We build and evolve LLM and matching systems that enhance Linked In’s understanding of members, jobs, and skills to improve relevance quality across job products. The team works closely with partner orgs to advance semantic retrieval, generative AI and efficient foundation model adaptation, ensuring that Linked In’s talent data is leveraged effectively and responsibly to drive long‑term business growth.

This is a high‑visibility team building AI solutions that directly impact millions of members.

At Linked In, 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 Linked In office on select days, as determined by the business needs of the team.

This role will be based in Sunnyvale, CA.

• Build and grow talent: Attract, mentor, and develop a diverse and high‑performing team of applied scientists and engineers. Foster an inclusive culture where people feel empowered to share ideas, take intelligent risks, and grow into technical leaders.
• Define clear direction: Translate product and business needs into a focused technical roadmap. Connect daily team work to Linked In’s broader mission and long‑term strategic priorities.
• Advance LLM and matching systems: Guide the team in developing and improving hybrid retrieval systems, and domain‑tuned LLM applications. Leverage Linked In’s unique data to ground model outputs, enhance job matching relevance, and improve end‑to‑end quality.
• Ensure scalability and efficiency: Partner with infra and platform teams to optimize retrieval and serving efficiency, including embedding optimization, adaptive caching, and parameter‑efficient fine‑tuning.
• Promote alignment and collaboration: Work across teams to identify shared opportunities, align on long‑term goals, and drive consistent progress. Proactively address misalignments with clarity and empathy.
• Foster innovation and inclusion: Create an environment that values curiosity, diverse perspectives, and open dialogue. Encourage the team to challenge assumptions, experiment responsibly, and continuously raise the technical bar.

• 7+ years of relevant professional experience.
• 3+ years of management experience.
• Bachelors in Computer Science or other technical discipline, or related practical technical experience.

• 10+ years of relevant work experience.
• Prior experience leading teams of 10‑20 individuals, including multiple Tech Leads.
• PhD in Computer Science, Machine Learning, Statistics or related fields.
• Experience leading teams in machine learning, NLP, or retrieval systems.
• Strong technical background in LLMs, retrieval architectures, and relevance optimization.
• Familiarity with semantic search, vector databases, or efficient model adaptation.
• Proven ability to connect technical strategy to business goals and communicate across disciplines.
• Passion for developing talent and building highly collaborative teams.

• Team Management
• AI System Design (Recommendation, Relevance, and Retrieval)
• Technical Leadership