Sr. Machine Learning Engineer, LinkedIn Premium

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.

The Premium AI teams work on many highly visible products at LinkedIn, which impact millions of LinkedIn members with the specific focus on Premium users. On the Premium AI team, you will be working on exciting products, such as Top applicant Job, Profile customization, Unified User Acquisition Management, Dynamic pricing, which use a diverse set of technologies, such as Deep Learning, NLP, Generative AI, AI agent and Multi-task learning. The Premium AI team partners with many critical AI teams at LinkedIn to build a better experience and accelerate. On the Premium AI team, you will have a chance to work with (and learn from) other Data teams, such as Generative AI, Notifications, Job Recommendations, Small business.Responsibilities:

As a senior software engineer in AI you will be responsible for building and deploying relevance models that power our various recommender systems and personalized intent engines, keeping scalability and performance in mind through your design and engineering choices. You will explore novel approaches for machine learning ranking and modeling downstream impact, as well as new ways of creating new product features by leveraging the cutting edge machine learning techniques in Generative AI, NLP. You will work with big data and analyze tracking data to understand member preferences and identify opportunities for taking the products you work on to the next level. You will work directly with partner data science, product, and infrastructure teams to take your ideas from conception to production.

_

This role will be based in Sunnyvale, San Francisco, Bellevue or New York City. 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.

LinkedIn's Machine Learning Engineers are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms. Unlike other companies that separate these roles, our engineers work on projects from ideation to implementation.

Responsibilities

• Work with BIG data, crunching millions of samples for statistical modeling, data mining, recommendation solutions
• Write production quality code and influence the next generation of LinkedIn's system
• Collaborate with 10+ machine learning engineers to deliver impact on LinkedIn newsfeed
• Build scalable AI innovations with foundation and infra partners

Basic Qualifications

• BA/BS Degree in Computer Science, Machine Learning or related technical discipline, or related practical experience.
• 2+ years experience in software design, development, and algorithm related solutions.
• 2+ years experience in programming languages such as Java, Python, etc.
• 2+ years experience with machine learning, data mining, and information retrieval or natural language processing

Preferred Qualifications

• 4+ years of relevant machine learning experience
• MS or PhD in Computer Science or related technical discipline
• Working knowledge in one or more of the following: machine learning, data mining, information retrieval, security data science, advanced statistics or natural language processing.
• Experience with iterative, test-driven development.
• Experience with configuration management (SVN, GIT, ant, maven, etc.).
• Experience with developing and designing consumer-facing products.
• Experience with Hadoop, Pig, or other MapReduce paradigms.
• Knowledge of internals Lucene/SOLR or other information retrieval systems.
• Published work in academic conferences or industry circles.

Suggested Skills

• Experience in Machine Learning and Deep Learning
• Experience in Big Data
• Strong technical background & Strategic thinking
• Experience in GAI and/or LLMs

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 $139,000 - $229,000. 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 

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.

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.