Staff AI Engineer

LinkedIn; California (MO); Hybrid; USD 170,000 - 277,000; Full time

Benefits offered by this job

Health and wellness programs

Time off and flexible vacation

Stock and bonus opportunities

Job summary

LinkedIn is seeking a Staff Machine Learning Engineer to develop and train cutting‑edge ML models that tailor recommendations for members’ activities. You will join a team of engineers delivering models from ideation to deployment.

The role involves building scalable AI solutions, collaborating with many ML engineers, and producing impactful results across LinkedIn’s feed and features.

Qualifications

• Bachelor's degree in Computer Science or related field, or equivalent practical experience.
• 4+ years of industry experience in software design and algorithms.
• 4+ years programming in Java or Python.
• 4+ years experience with machine learning, data mining, information retrieval, or NLP.

Responsibilities

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

Skills

Big data

Java

Python

Machine learning

Data mining

NLP

Spark

TensorFlow

Leadership

Mentorship

Education

Bachelor's degree in Computer Science or related technical field

MS or PhD in Computer Science or related technical discipline

Tools

Spark

TensorFlow

Java

Python

Job 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.

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.

As a Staff Engineer at LinkedIn, you will be responsible for the development and training of cutting‑edge machine learning models and algorithms that can effectively leverage our members' platform activities and industry trends to create personalized recommendations that are delivered to our members at the optimal moment.

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

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

Preferred Qualifications:

• 6+ years of relevant machine learning experience
• MS or PhD in Computer Science or related technical discipline
• Experience with machine learning, optimization algorithms, deep-learning techniques
• Experience developing large scale systems
• Experience with Spark, Tensorflow and Java.
• Previous leadership or mentorship experience is preferred
• Ability to diagnose technical problems, debug code, and automate routine tasks
• Analytical approach coupled with solid communication skills and a sense of ownership
• Track record of producing papers in conferences such as KDD, WWW, WSDM, and Patenting Innovations

Suggested Skills

• Experience leading engineers to tackle a large-scale AI problem
• Strong technical background & Strategic thinking
• Experience in Machine Learning, Big Data and Deep Learning
• Experience in GAI and/or LLMs

You will Benefit from our Culture

• 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 $170,000-$277,000.
• 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.

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 and Compliance Posters for Job Candidates

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: https://www.linkedin.com/legal/candidate-portal.

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.