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60 Linkedin Data Center Engineer Jobs Hiring Near You

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture ... Define durable integration patterns across AEM Guides, Help Center, CRM systems, content data ...

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture ... You will partner closely with product, engineering, analytics, and business leaders to understand ...

The Production Backbone Network Engineering team is responsible for architecting, building, and operating LinkedIn's global Backbone and Edge network infrastructure that connects our data centres ...

The Production Backbone Network Engineering team is responsible for architecting, building, and operating LinkedIn's global Backbone and Edge network infrastructure that connects our data centres ...

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture ... You will partner closely with product, engineering, analytics, and business leaders to understand ...

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture ... Define durable integration patterns across AEM Guides, Help Center, CRM systems, content data ...

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Do people at LinkedIn recommend working with their team?

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Do people get enough training when they start at LinkedIn?

Most people got enough training when they started.
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What are the most popular categories at Linkedin?
Infographic showing various Data Center Engineer job openings at Linkedin in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 74% Physical, 18% Hybrid, and 8% Remote job distribution.
Senior Staff AI Engineer, Network Growth AI

Senior Staff AI Engineer, Network Growth AI

LinkedIn

Mountain View, CA • On-site

$122K - $168K/yr

Full-time

Posted 12 days ago


LinkedIn rating

9.3

Company rating: 9.3 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies


Job description

Company Description
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.
Job Description
Location:
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 based in Sunnyvale, CA.
Team Overview:
The Network Growth and Relationship AI team is at the forefront of creating cutting-edge, AI-powered solutions that drive meaningful connections and foster professional growth. Our team builds scalable machine learning models and advanced AI systems that help millions of LinkedIn members expand their networks, discover new opportunities, and deepen professional relationships. By leveraging vast data and deploying sophisticated algorithms, we enhance member experience with personalized recommendations, insights, and connections that transform their career paths. Our recommender systems have adopted the latest modeling techniques including Sequence Modeling, LLM, EBR, GNN, etc, and we're continuing our journey as the modeling innovation pioneer at LinkedIn to build both ranking and retrieval models that impact the entire LinkedIn ecosystem.
The Network Growth AI team is highly impactful and is in charge of optimizing member value, helping them to build relationships on LinkedIn and advance their professional network. The team works in close collaboration with the product, engineering and data science team and has a very exciting roadmap ahead. If you are looking to lead a highly visible team that operates at a fast pace, works on exciting research problems and delivers great results every quarter, Network Growth AI is the place you should look. We also publish in top machine learning conferences.
Responsibilities:
As a senior technical leader in the Network Growth AI team, you will directly impact member experience through optimizing the above dimensions. You will be responsible for leading a team of scientists and machine learning engineers that build and own personalization 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. You will be leading the core modeling initiatives in the team, including our efforts in Generative Recommendation, Large Language Models, Graph Neural Networks, and Sequential Models. You are expected to challenge the status quo on AI, Engineering, and Product fronts, propose innovative new ideas, and lead these new initiatives to production to further improve our member experience and drive value.
  • You will be responsible for team's core modeling effort and our mid/long term direction
  • As a hands-on tech lead, you are expected to actively participate in key technical and design discussions with technical leads in the team.
  • Collaborate with platform engineering, product, data science and partner teams to design machine learning solutions to power Network Growth ecosystem and optimize member experience.
  • Operate best engineering and scientific practices & processes to ensure productivity of the team and drive faster iterations via A/B experiments.
  • You will be expected to be a role model and professional coach for engineers with a strong bias for action and focus on craftsmanship.
  • You will work with peers across teams to support and leverage a shared technical stack.
  • You will coach the team to produce high-quality software that is unit tested, code reviewed, and checked in regularly for continuous integration.

Qualifications
Basic Qualifications:
  • 2+ years of experience as a Technical Lead
  • 5+ years of overall industry experience in AI / Machine Learning
  • Bachelor's, Master's, or PhD Degree in Computer Science, Machine Learning, or related technical discipline or equivalent practical experience

Preferred Qualifications:
  • 10+ years of industry experience.
  • 4+ years of technical leadership (Staff+) experience, including recent experience at the Senior Staff / L7 / Principal Engineer level.
  • Ph.D. in Computer Science, Machine Learning, Natural Language Processing, or a related discipline.
  • Prior experience with large scale ML data infrastructure
  • Experience with developing and designing production scale recommender system products.
  • Published work in academic conferences or industry circles.

Suggested Skills:
  • AI Recommendation Systems
  • Transformer Models
  • Technical Leadership

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.
Compensation:
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $191,000 - $315,000. 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.
Additional Information
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 and describe the specific Accommodation requested for a disability-related limitation.
Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36
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.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
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
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.

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