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:
This role is a part of our LinkedIn Ads AI team and will be responsible for leading roughly 20 engineers (with one manager reporting to this person in addition to multiple technical leads). The team includes both AI/ML and Full Stack engineers who build algorithms models and systems that power our Ad Tech platform and products.
Some of our next generation AI solutions include building a new B2B recommendation engine which leverages LinkedIns economic graph to drive new and better results related to identity engagement and buyer data for our Ads products.
LinkedIn Ads is a multi-billion dollar revenue stream for the organization and is a highly successful product area.
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 closedwon 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 realworld 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:
Masters 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
Technical Strategy
Additional Information :
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.
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Compensation:
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198000 - $326000. 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: 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.
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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:
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 LinkedIns 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: Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: Work :
No
Employment Type :
Full-time
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