AI Engineer

Company Description

LinkedIn is the worlds 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. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.

Job Description

This role will be based in Sunnyvale, San Francisco, 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.

Responsibilities:

AI is at the core of how LinkedIn connects more than a billion members to opportunity across jobs, sales, marketing, content, and trust platforms. As an AI Software Engineer you will own end-to-end machine learning systems that run in production at LinkedIn scale. You won't just train models, you will own the recommender and classification system that power LinkedIn’s core products. Your responsibilities cover the full product lifecycle from translating product requirements into system design, training the models to power the system, driving the experiments that prove efficacy, and managing the GPU fleets that run them at scale in milliseconds; you are the engine that drives value for our members.

This is an individual-contributor role; we expect you to be the owner of a well-defined significant workstream, align technical direction within your team, review code and technical designs from your team, and to deliver measurable member and business impact with a sense of urgency.

What success looks like in your first year

• Grow to the owner of an AI workstream end to end and ship at least one model-based system to a measured impact on member or business value.
• You become the go-to point of contact for your domain within our team and help others onboard to it as needed.
• Implement an efficiency or quality improvement (i.e. inference/training efficiency, engineer velocity, or tech-debt removal) backed by data.

• You operate systems reliably as on-call and work with senior engineers to root-cause at least one significant production regression.

Why LinkedIn

You'll work on AI systems with immediate, measurable impact on more than a billion members, alongside engineers who set the industry bar for recommendation systems at scale powered by the latest open source generative models and GPU inference. We encourage staying up to date on industry state-of-the-art and sharing your work with the community through conference, journal, and blog publications. We invest in your growth with real mentorship, we trust you with real ownership, and we measure what matters: impact, not output according to our core engineering principles.

• Impact: quantify the value you created for members, the business and your team
• Leadership : communicate and lead through influence, not authority
• Execution: deliver impact with a sense of urgency
• Craft: innovate and create leverage with high-quality solutions

Qualifications

Basic Qualifications

• Bachelor's degree in Computer Science or related technical field or equivalent technical experience
• 1+ years experience with machine learning, data mining, and information retrieval or natural language processing
• 1+ year of industry experience in software design, development, and algorithm related solutions.
• 1+ years experience in programming languages such as Java, Python, etc.

Preferred Qualifications

• 2+ years of relevant AI/Machine Learning experience.
• MS in Computer Science or related technical discipline
• Experience with PyTorch or similar Deep Learning frameworks
• Experience with Spark for data manipulation and transformation
• Experience with A/B testing at scale in a consumer-facing product
• Experience with AI code development (i.e ClaudeCode, Codex, Copilot)
• Experience adapting pre-trained LLMs to production systems including fine-tuning and student-teacher model paradigms
• Published work in academic conferences or industry circles.

Suggested Skills

• Data Mining
• Data Coding
• Machine Learning

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 $120,000 - $195,000. 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

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:

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:

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Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters:

Workplace Type: HybridCareer Track & Grade: IC2/7Department: Engineering