Sr. AI Engineering Manager, Ads AI

LinkedIn

Mountain View (CA)

Hybrid

USD 198,000 - 326,000

Full time

6 days ago
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Job summary

LinkedIn is seeking a Senior Engineering Manager for the Ads Attribution & Companies team in Mountain View. The role oversees end-to-end measurement, privacy-safe signal integration, attribution, and experimentation while scaling the Companies data platform.

You will set vision, drive roadmaps, and mentor an inclusive engineering team to deliver reliable, high-impact APIs. The position requires deep ads measurement/attribution, production ML, and large-scale distributed data systems, with bonus

Qualifications

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

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.

Skills

AI Modeling - LLMs
Change Management

Education

Bachelor's in Computer Science or related field
PhD in CS/ML/Statistics or related fields

Job description

LinkedIn 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.

Job Description

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.
Qualifications
Basic Qualifications

Bachelor'sin 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
  • 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. For additional information, visit: https://careers.linkedin.com/benefits.

Additional Information
Equal Opportunity Statement

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a Reasonable Accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us and describe the specific Accommodation requested for a disability-related limitation. Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

  • Documents in alternate formats or read aloud to you
  • Having interviews in an accessible location
  • Being accompanied by a service dog
  • Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement

As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.

Global Data Privacy Notice and Compliance Posters for Job Candidates

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.

By clicking the link above or any third‑party link within this posting, you are leaving this site and going to a third‑party website where the third‑party website's terms and privacy policy apply

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