About this role
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 is not eligible for visa sponsorship. Applicants must be authorized to work in the US for LinkedIn without requiring visa sponsorship now or in the future.
To learn more about the program and the application questions and timeline, please visit: careers.linkedin.com/reach. Searching for your dream job?
At LinkedIn, we have developed an apprenticeship program that creates opportunity for every individual with the passion, potential, and drive to either develop or restart their career in engineering. We fundamentally believe top talent can come from anywhere, regardless of educational training or professional experience.
REACH is a multi-year program where individuals with passion for engineering will work in technical roles to build their skill set and gain the experience needed to become an Engineer at LinkedIn. The time each apprentice spends in this program will vary depending on their incoming skill set, experience, and progress through the program. The time in program is a one year minimum and a five year maximum in the apprenticeship. This program is designed for candidates who have non-traditional career paths and we strongly encourage those candidates to apply. This includes but is not limited to: candidates without Computer Science degrees who are self-taught, those that are re-entering the workforce, individuals switching careers, or those who have attended boot camp style courses focusing on machine learning or data science.
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.
As an Apprentice Engineer, you will be placed on an Artificial Intelligence/ Machine Learning engineering team at LinkedIn developing cutting-edge machine learning models that serve millions of members. You will learn from fellow engineers and leaders and develop key skills applicable to a career in Artificial Intelligence/Machine Learning. Furthermore, apprentices are guaranteed a percentage of time to focus on their personal technical development, using both LinkedIn’s internal ecosystem and external educational opportunities.
Is Artificial Intelligence/ Machine Learning a good fit for me? You might be a good fit for this apprentice role if you have strong quantitative and problem-solving skills, regardless of the areas in which you developed them or applied them. There are endless possibilities for the experiences that have prepared you for this apprenticeship. For example, you might be someone working in analytics or software engineering who has been wanting to switch to artificial intelligence/ machine learning. You might be someone with a background in social science who has applied quantitative methods in that arena. You might be someone whose hobby is thinking about improvements to sports statistics like expected goals, home runs, or team rankings.
Qualifications
Basic Qualifications:
• An undergraduate or graduate degree (bachelor’s, master’s or doctorate) in any field
• Demonstrated history of independent problem solving, data-driven thinking, and quantitative skills. These skills may have been gained or demonstrated as part of a degree program or prior work experience. These do not have to be in a technology setting, but rather any situation in which you used math and code to help drive decisions or outcomes.
Preferred Qualifications:
• Demonstrated history of Artificial Intelligence/Machine Learning related projects. There is a wide range of examples that will qualify, including but not limited to
• Open-source contributions
• Personal analytics or machine learning projects
• Analytical, mathematical, or statistical work as part of a job or research
• Understanding of CS concepts: variables, recursion, algorithms, data structures, object orientation, error handling, etc. Knowing these will make it easier for you to learn more complex software topics!
• Knowledge of common machine learning techniques such as regression, clustering, and tree-based methods
• Excellent collaborative and communication skills, and ability to clearly articulate your perspective
• Entrepreneurial mindset to bring in a new and unique perspective to the team
• Desire to learn and develop skills in the fields of artificial intelligence/ machine learning
Suggested Skills
• Statistical Analysis
• Machine Learning
• Coding in Programming/scripting languages
• Critical Thinking
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $82,000 to $109,000. 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.
• Application Process + Requirements*
Click “I’m interested” to fill out the initial application form. After you apply, you’ll receive an email with a link to our essay application questions. You’ll have until the application deadline to submit your responses.
Our application process is designed to give individuals the opportunity to show us a range of qualities we believe will make them successful engineers. This includes their drive and ability to learn, tenacity and work ethic, unique perspective and passion for engineering. As part of the application process, individuals are required to submit responses to the application questions and responses will be reviewed for completeness as well as content. To review the questions, including recommended length for each, please visit the role description at careers.linkedin.com/reach. Please note, resumes and LinkedIn profiles will NOT be considered as part of the evaluation for REACH. Therefore, please make sure that any information you would like us to know is highlighted in your application responses. We also know that tools like ChatGPT and others are widely used and can be helpful in organizing your thoughts. If you choose to use AI while writing your application, please make sure your responses reflect your own experiences, voice, and ideas. We’re looking to understand your journey, interests, and baseline technical skills- and authenticity really helps us get to know you.
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 at 
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.
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Educational level:
Level of experience (years):
Senior (5+ years of experience)