LinkedIn 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.

　　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 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.

　　The Ads Ranking team is responsible for building and applying ML/AI solutions in the fast growing Marketing Solutions business ($5.5B+) at LinkedIn. As a Sr. Staff Software Engineer, you will be responsible for solving cutting-edge AI problems that empower large & small businesses to reach, engage, and convert professional audiences at scale. This role covers a number of challenges around: ranking personalization for multiple Ad formats, multiple placements across LinkedIn, varying objectives (Click, Video View etc), UI optimization (bandits), Visual optimization of Ads content (custom generative-AI/LLMs and content recommendations) and working in near real-time (by understanding user, campaigns and content). The team works on diverse modeling problems across deep-learning, multi-objective optimization, multi-modal content models and large parameter model training and low-latency systems to gather data + execute models in near real-time to over 1 billion LinkedIn members.

　　Responsibilities:

　　Work with large-scale data to build systems which will leverage and support new AI techniques for image & text generative models, multi-task learning, transfer learning, content understanding, deep learning, entity embedding and algorithms to optimize member experience and advertiser ROI in the marketplace.

　　Provide technical leadership to junior engineers and collaborator orgs, drive and perform best engineering practices to initiate, plan, and execute large-scale, cross-functional critical projects.

　　Hold the team to a high ML craftsmanship bar and actively reduce ML tech debt, designing systems that scale with algorithms and with time, and improve engineering productivity.

　　Partner with data science & analytics teams, product & infrastructure teams to build new revenue and engagement driving ideas.

　　Bring together industry research and develop opportunities to contribute back to industry research

　　Basic Qualifications:

　　-BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience

　　-5+ years of industry experience in software design, development, and algorithm related solutions

　　-5+ years experience programming languages such as Java, C/C++, Python

　　-2+ years in an architect or technical leadership position

　　-Experience with Machine Learning or Recommendation Systems

　　Preferred Qualifications

　　PhD in Computer Science, Machine Learning, Statistics or related fields

　　10+ years of experience in AI/Machine Learning and Generative/Transformer Models

　　Strong academic credentials with publications in top-tier journals and conferences

　　Background in one or more of the following areas: deep learning, knowledge graph, information retrieval, natural language processing, optimization, image/text generation

　　Experience in building AI models and systems

　　Experience in large language and deep neural network models

　　Experience applying AI models and systems to a large operations-heavy business

　　Demonstrated ability to work with peers in engineering across teams to set technical directions

　　Track record of producing research papers and/or earning patents

　　Suggested Skills:

　　-Deep learning models and Transformers

　　-Machine Learning

　　-Product design and leadership

　　-Recommendation systems

　　-Information retrieval

　　LinkedIn is committed to fair and equitable compensation practices.

　　The pay range for this role is $180,000 to $300,000. 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.

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　　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

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　　-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.

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