Sr. AI Engineering Manager, Ads AI

About the role

This role will be based in Mountain View.

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.

We're hiring a Senior Engineering Manager to lead LinkedIn's Ads Attribution & Companies team. You'll own end-to-end measurement and modeling for advertiser outcomes - privacy-safe signal integration, multi-touch attribution, conversion modeling, and experimentation - while scaling the Companies data platform that powers insights across LinkedIn.

You'll set vision and roadmap, partner closely with Product, Data Science, Sales, and Legal, and deliver reliable, high-impact systems and APIs. You'll grow and mentor an inclusive, high-performing engineering team and build a culture of clarity, ownership, and excellence.

What you'll bring

deep experience in ads measurement/attribution, production ML (causal inference, propensity, experimentation), and large-scale distributed data systems; a track record of shipping high-quality, resilient services; and strong cross-functional leadership. Bonus: B2B data, identity graphs, offline conversions, and MMM.

If you're excited to build the measurement backbone for LinkedIn Ads and make our companies ecosystem smarter for millions of members and customers, we'd love to talk.

Responsibilities

• Develop a strategy for a new technical foundation based on using AI/LLMs to innovate in ad recommendation platforms.
• Design a technical solution with actionable recommendations across Marketing and Sales ecosystems, creating a unified data flywheel that compounds value by learning from advertiser outcomes and CRM closed-won signals.
• Evangelize the use of LLMs and AI in software development in the broader organization with robust experimentation and measurement frameworks that tie model performance directly to business outcomes, not just offline or proxy metrics.
• Technical vision, execution standards, and mentorship that raise the bar for applied ML rigor, system reliability, and real-world impact across the team.
• Partner with infra and platform teams to optimize retrieval and serving efficiency, including embedding optimization, adaptive caching, and parameter-efficient fine-tuning.
• Attract world class talent and provide technical guidance, career development, and mentoring to team members.
• 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.

Basic Qualifications

• Bachelor's in Computer Science or related technical field or equivalent technical experience
• 7+ years of industry experience
• 3+ years people management experience

Preferred Qualifications

• 10+ years of relevant work experience including 4+ years of leadership experience
• PhD in Computer Science, Machine Learning, Statistics or related fields
• Experience with retrieval and context-heavy reasoning (RAG), fine-tuning small language models (SLMs), and customizing deep learning models for Ads ranking, retrieval, budget forecasting and control, and low latency tasks

Suggested Skills

• AI Modeling - LLMs
• People Leadership
• Change Management

You will Benefit from our Culture

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

Compensation

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 - $326,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans.