Engineering Manager - Monetization Relevance - Sunnyvale, CA
Are you passionate about text mining, information retrieval, and machine learning? Do you enjoy leading engineers that design algorithms, build models, and move metrics by applying these techniques to solve real world problems that improve the lives of hundreds of millions of professionals?
As an Engineering Manager on the Monetization Relevance Team you will be responsible for leading a team of data scientists and relevance engineers that build and own recommendation algorithms, models, and systems. You will work with some of the best engineers and scientists on state-of-the-art technology that leverages truly big data.
LinkedIn's relevance systems process semi-structured content in the 400+ million member profiles and match them with job descriptions, company profiles, and professional insights to drive rich user experiences in LinkedIn's paid products. These algorithms and systems power relevance features like recommendations and search in LinkedIn products such as LinkedIn Talent Solutions (e. . Recruiter and Referrals), LinkedIn Marketing Solutions (eg. Ads) in the LinkedIn Feed, and LinkedIn Sales Solutions (Sales Navigator). In addition, these algorithms and systems also power unique insights and subscription based products like Premium insights, LinkedIn Learning/Lynda. , and LinkedIn ProFinder.
LinkedIn was built to help professionals be more productive and successful in their careers. Every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world's workforce in ways no other company can.
Responsibilities: As a hands-on manager participate in key technical and design discussions with technical leads in the team Collaborate with application engineering, product, and marketing teams to design relevance features and define product strategy for monetization products such as Recruiter, Sales Navigator, Native Ads, Premium Insights, LinkedIn feed, and LinkedIn Learning Ownership of feature engineering, recommendation and search services and pipelines, and A/B experimentation that enable and drive rich daily use-cases for LinkedIn members Attract world class talent and provide technical guidance, career development, and mentoring to team members
Basic Qualifications: Experience leading a team of engineers as a people manager Masters Degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or related discipline. Experience in Java, C++, or another object-oriented language. Experience using at least one of the following clustered computing systems: MapReduce, Dataflow, Hadoop/Cosmos/Spark, Lucene/SOLR or Storm/Samza.
Preferred Qualifications: 2+ years of management experience Ph. . in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or related discipline. Worked with web-scale traffic and data. Experience with developing and designing monetization and enterprise products. Published work in academic conferences or industry circles.
A little about us:
LinkedIn's vision is to create economic opportunity for every member of the global workforce. Our employee talent is our #1 operating priority.