Sr. AI Engineering Manager, Ads AI

LinkedIn • Mountain View, CA

2d • Hybrid

About The Position

LinkedIn is hiring a Senior Engineering Manager to lead its Ads Attribution & Companies team. The role owns end-to-end measurement and modeling for advertiser outcomes, including privacy-safe signal integration, multi-touch attribution, conversion modeling, and experimentation. It also scales the Companies data platform that powers insights across LinkedIn. The manager sets the team’s vision and roadmap, partners with Product, Data Science, Sales, Legal, and other teams, and delivers reliable, high-impact systems and APIs.

The position also develops a technical foundation using AI and large language models to innovate in ad recommendation platforms. It designs solutions that connect Marketing and Sales ecosystems into a unified data flywheel, learning from advertiser outcomes and CRM closed-won signals. The role promotes AI-assisted software development and robust experimentation and measurement that connect model performance to business outcomes. It provides technical direction, execution standards, and mentorship while building and developing an inclusive, high-performing team.

The role is based in Mountain View and is hybrid, with work performed both from home and from a LinkedIn office on select days, according to business needs.

Requirements

• Bachelor’s degree in Computer Science or a related technical field, or equivalent technical experience.
• At least 7 years of industry experience.
• At least 3 years of people management experience.
• Deep experience in ads measurement or attribution, production machine learning, and large-scale distributed data systems.
• Experience with causal inference, propensity, and experimentation in production ML.
• Track record of shipping high-quality, resilient services.
• Strong cross-functional leadership.

Nice To Haves

• At least 10 years of relevant work experience, including at least 4 years of leadership experience.
• PhD in Computer Science, Machine Learning, Statistics, or a related field.
• 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.
• Experience with B2B data, identity graphs, offline conversions, and marketing mix modeling (MMM).

Responsibilities

• Lead LinkedIn’s Ads Attribution & Companies team and own end-to-end measurement and modeling for advertiser outcomes.
• Scale the Companies data platform that powers insights across LinkedIn.
• Set the team’s vision and roadmap, partnering with Product, Data Science, Sales, Legal, and other teams.
• Deliver reliable, high-impact systems and APIs.
• Develop a strategy for a new technical foundation using AI and LLMs to innovate in ad recommendation platforms.
• Design technical solutions with actionable recommendations across Marketing and Sales ecosystems, creating a unified data flywheel informed by advertiser outcomes and CRM closed-won signals.
• Promote the use of LLMs and AI in software development across the organization, supported by robust experimentation and measurement frameworks tied to business outcomes.
• Set technical vision and execution standards and mentor the team to improve applied ML rigor, system reliability, and real-world impact.
• Partner with infrastructure and platform teams to optimize retrieval and serving efficiency, including embedding optimization, adaptive caching, and parameter-efficient fine-tuning.
• Attract talent and provide technical guidance, career development, and mentoring to team members.
• Create an environment that values curiosity, diverse perspectives, and open dialogue; encourage responsible experimentation and continuous improvement.

Benefits

• Generous health and wellness programs.
• Time away for employees of all levels.
• The total compensation package may include an annual performance bonus, stock, benefits, and/or other applicable incentive compensation plans.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior