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Hybrid · Mountain View, California, United States$204k–337kFull-timePosted 2 months ago
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.
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 either Sunnyvale, CA or New York, NY.
Team Overview:
The Video AI team sits at the heart of our LinkedIn’s ambitious growth strategy. Our team is a dynamic group of machine learning experts dedicated to revolutionizing the way we interact with video content. This team is at the forefront of developing cutting-edge artificial intelligence technologies that enhance video understanding, search, and personalization. By leveraging state-of-the-art AI techniques, the Video AI team is poised to open up new ways of engaging with videos on LinkedIn.
Our work encompasses a range of applications, from real-time video analytics to intelligent content recommendation systems, positioning our company as a leader in the rapidly evolving landscape of video technology. As LinkedIn continues to revolutionize our market presence, the Video AI team’s expertise will be instrumental in shaping our product offerings and achieving our strategic goals, ensuring we stay ahead of the competition and deliver unparalleled value to our 1 billion+ global users.
Below are a few examples of the problem spaces we work in (and much more!):
Video Understanding: Building state of the art content understanding models and content embeddings to power all video use cases.
Video Feed Personalization: Identifying the most engaging content and distributing to users.
Video Search: Tackling the multimodal search problem, delivering videos that provide the highest user value.
Video Safety: Safeguarding users from malicious actors and content, building an open and safe community for all.
Responsibilities:
As a Senior Engineering Manager you will lead a team of 15-20 engineers and technical leads. You will drive technical strategy, execution, professional growth, and collaboration across the team.
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 LinkedIn’s broader mission and long-term strategic priorities.
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.
Basic Qualifications:
3+ years of management experience, leading team(s) of direct reports.
7+ years of relevant professional experience in AI/ML Engineering and/or leadership of AI/ML Engineering teams.
Bachelors in Computer Science or other technical discipline, or related practical technical experience
Preferred Qualifications
4+ years of prior experience leading AI engineering teams, with leadership of 15+ total reports.
10+ years of relevant professional experience in AI, Machine Learning, or a related field.
PhD or Master's in Computer Science, Machine Learning, Statistics or related fields
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.
Suggested Skills:
People Leadership
AI Engineering
Machine Learning
Technical Strategy
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 $204,000 - $337,000. 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.
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.
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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.
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