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LinkedIn

Staff Engineer - ML Systems (CoreAI)

LinkedIn, Mountain View, California, us, 94035


Staff Engineer - ML Systems (Core AI)

Company OverviewLinkedIn is the world’s largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters.

Team OverviewLinkedIn’s Core / Foundational AI organization stands as the innovation epicenter, addressing the fundamental AI challenges and the force behind LinkedIn's next-generation AI-driven member experiences. Our mission spans across the entire marketplace, leveraging our expertise in data curation, algorithm development, and robust infrastructure to spearhead AI innovations. We are dedicated to creating a transformative impact on all LinkedIn products, establishing the platform as a leader in the AI realm.

LocationAt LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.

This role will be based in Sunnyvale, CA.

ResponsibilitiesAs a Staff Engineer at LinkedIn, you will be responsible for the development and training of cutting-edge machine learning models and algorithms that can effectively leverage our members’ platform activities and industry trends to create personalized recommendations that are delivered to our members at the optimal moment.* Work with big data, crunching millions of samples for statistical modeling, data mining, and recommendation solutions* Design system architecture, implement scalable data pipeline and serving service, write production quality code and influence the next generation of LinkedIn’s system* Collaborate with a team of 10+ machine learning engineers to deliver high-impact solutions across LinkedIn* Build scalable AI innovations with foundation and infra partners

Will work hands-on to build (code) and implement solutions.

Provide technical leadership to team and drive cross-functional communication

Basic Qualifications4+ years of industry experience in system design, development, and algorithm related solutions.4+ years of coding experience utilizing programming languages such as Java, Python, or Scala4+ years experience with data engineering, data infrastructure, and/or machine learningBachelor’s degree in Computer Science or related technical field or equivalent practical experience

Preferred Qualifications7+ years of relevant industry experienceHands on experience of building a large scale online recommender system from end to end to serve a critical productHands on experience the internals of deep learning frameworks (e.g. PyTorch, TensorFlow) and deep learning modelsGeneral experience with the training and deployment of ML modelsHands on experience with writing CUDA code and knowledge of GPU internalsMS or PhD in Computer Science or related technical disciplineExperience with distributed systems development or distributed ML workloads

Suggested SkillsDistributed SystemsMachine Learning InfrastructureDeep Learning Frameworks & Models

You will Benefit from our CultureWe 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 $200,000 - $268,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.

Equal Opportunity StatementLinkedIn 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: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.

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 accommodations@linkedin.com 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.

Pay Transparency Policy StatementAs a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.

Global Data Privacy Notice for Job CandidatesThis document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice