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LinkedIn Software Engineering Manager - AI Training & Infrastructure in Mountain View, California

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.

This role will be based in Sunnyvale, CA.

At 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 both 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.

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.

Join us to push the boundaries of scaling large models together. The team is responsible for scaling LinkedIn’s AI model training with hundreds of billions of parameters for all AI use cases from recommendation models, large language models, to computer vision models. We optimize training performance across algorithms, AI frameworks, infrastructure software, and hardware to harness the power of our GPU fleet with thousands of latest GPU cards. The team also works closely with the open source community and has many open source committers (TensorFlow, Horovod, Ray, Hadoop, etc.) in the team. Additionally, this team focussed on technologies like LLMs, GNNs, Incremental Learning, Online Learning for Training infrastructure.

Responsibilities

  • Owning the technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems.

  • Designing, implementing, and optimizing the performance of large-scale distributed training for personalized recommendation as well as large language models.

  • Improving the observability and understandability of various systems with a focus on improving developer productivity and system sustenance.

  • Mentoring other engineers, defining our challenging technical culture, and helping to build a fast-growing team.

  • Working closely with the open-source community to participate and influence cutting edge open-source projects (e.g., PyTorch, GNNs, DeepSpeed, Huggingface, etc.).

  • Functioning as the tech-lead for several concurrent key initiatives for the Training Infrastructure and defining the future of AI training platforms.

Basic Qualifications

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

• 1+ years of experience in software engineering/technical management and people management.

• 5+ years of industry experience in software design, development, and large-scale software engineering

• Experience programming in object-oriented and/or functional programming languages(like Java/CPP/Scala/etc.)

• Hands on experience developing distributed systems, databases, large scale data systems and/or Backend API'

Preferred Qualifications

MS or PhD in Computer Science or related technical discipline

2+ years of hands-on software engineering/technical management and people management experience

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

5+ years programming experience in languages such as Java, C/C++, C#, Python, Go, etc.

Suggested Skills:

  • Technical Leadership

  • People Management

  • Stakeholder Management

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $156,000 to $255,000. 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 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: 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 Statement

As 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 Candidates

This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice

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