Director of Engineering, AI Foundations
LinkedIn was built to help professionals achieve more in their careers, and everyday 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. We are much more than a digital resume – we transform lives through innovative products and technology.
Creating economic opportunity for every member of the global workforce is a responsibility we all share. To truly transform the global economy, we must evolve the way we hire and enable our talent to serve people of all backgrounds and experiences. LinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer.
Technology leaders collaborate, maintain balance, commit and achieve results – all while upholding immense pride in their quality of work. Our leaders value their craft and inspire their team to do the same. They balance product and technology strategy to put members first. They are responsible for attracting, retaining, engaging and developing their teams while also leading and inspiring them to achieve the goals of LinkedIn. Engineering leaders are champions of LinkedIn to their coworkers, their networks and the tech community.
What you’ll do:
You will lead a team in charge of AI Foundations (AIF) at LinkedIn. The AIF team builds AI technology that is used horizontally across teams at LinkedIn, and is focused on core algorithms, and data assets. Examples include core technology support for Natural Language, Video, and Image Processing, large-scale Optimization methods, learning models (eg., GLMix, XGBoost, Deep Neural Networks), model health/monitoring, AI privacy, AI explainability, engineering productivity, and many others. This team primarily partners with AI vertical teams, AI/general infrastructure platform teams, and many other Data teams.
- Minimum of 8 years of experience building machine learning/data mining technology with technology and business impact.
- MS in Computer Science or related engineering/science experience
- PhD in Computer Science or related engineering/science experience
- Strong, demonstrated background in machine learning and data mining techniques
- Five or more years managing teams of 20+ individuals and managers
- Good understanding of large-scale engineering systems and some or all of big data technologies like Hadoop, Spark, Machine Learning, distributed key-value stores, streaming processes, workflow scheduler, recommender systems, statistical methods, experimental design.
- Experience leading by example and inspiring teams to perform at a very high level, collaborating very well across functions/teams.
- High motivation and ability a) to convert vague and ill-defined problems into well-defined problems, b) take initiative and encourage consensus building across the entire organization.
- Enthusiasm for solving interesting problems for real customers.
- Publications at top tier machine learning and related scientific conferences.
- A proven track record of delivering end-to-end solution for high QPS systems that require working with massive amounts of high frequency data.
- Strong leadership abilities in order to communicate and drive cross-functional efforts.
- Great relationship and people skills.
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
Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here. Please reference the Equal Employment Opportunity statement here and supplement here for more information.
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