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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.

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 hybrid in LinkedIn's Mountain View campus.

Our team is looking for a frontline manager to manage the data engineering team responsible for AI model experimentation, balancing the building of signal pipelines while optimizing the experiment development lifecycle. This person will manage a small team of engineers and collaborate closely with other data engineers working on other parts of the inference stack, as well as partners in AI, data science, and the information retrieval platform.

The ideal candidate has a strong tech background in large-scale AI recommendation systems, a passion for engineering craft and operational excellence, a track record of adapting to fast-changing technology, and experience growing engineers.

Responsibilities:

+ Build inference experiments, with the challenge of sparse signals, to improve content recommendations for new members, a critical project that has the attention of the CEO. Collaborate with other data engineers to enhance the inference stack in the process.

+ Partner with data scientists to innovate and build model evaluation tools based on a variety of data sets. This is an initiative that receives regular attention from VPs.

+ Work with a crack team of engineers across AI, data science, AI infrastructure, and data engineering to build a state-of-the-art Feed recommendation system that will transform how we do AI at LinkedIn

Basic Qualifications

+ BA/BS Degree in Computer Science or related technical discipline, or related practical experience.

+ 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training

+ 5+ years experience in software design, development, and algorithm related solutions.

+ 5+ years programming experience in object-oriented programming languages such as Python, Java, Javascript, C/C+

Preferred Qualifications:

+ Background in at least one of the following: large scale distributed systems, stateful backend systems, AI development of transformer models, recommender systems

+ Track record of adapting to fast-changing technology and leading others through similar changes

+ Passion for engineering craft and operational excellence

+ Experience growing strong engineers

+ Strong critical thinking skills and growth mindset

Suggested Skills:

+ Technical Leadership

+ Communication

+ Software Design

+ Cross-organizational collaboration

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. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $152,000 - $248,000. 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.

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 at [email protected] and describe the specific accommodation requested for a disability-related limitation.

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.

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

Pay Transparency Policy Statement ​

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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: https://legal.linkedin.com/candidate-portal.