Artificial Intelligence/ Machine Learning (AI / ML) Engineers at LinkedIn develop cutting-edge machine learning models impacting millions of members. The  AI /ML track may be a good fit for you if you have strong quantitative, analytical 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.

  • With a background in social science who has applied quantitative methods in that arena .

  • Whose hobby is thinking about improvements to sports statistics like expected goals, home runs, or team rankings. 

Explore Artificial Intelligence/ Machine Learning Further!

Apprenticeship Details Application Questions How To Apply FAQ

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 given a percentage of time to focus on their personal technical development, using both LinkedIn’s internal ecosystem and external educational opportunities. The time in program is a one year minimum and a five year maximum in the apprenticeship. 

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 both 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. 

This role is hybrid and will be based out of our Mountain View, CA office.

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. 

Job Responsibilities: 

  • Contribute a unique perspective and creative approach to solving problems at LinkedIn
  • Continue to learn and develop artificial intelligence/ machine learning skills
  • Under the mentorship and guidance of seasoned LinkedIn engineers, produce high-quality software that is tested, code reviewed, and checked in regularly for continuous integration
  • Solve difficult problems with machine learning, write code to put those solutions into production or inform business decision making, and deliver with an appropriate amount of urgency and quality
  • Develop machine learning models that will serve our 740 million members on LinkedIn.com

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.
  • 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

 

Preferred Qualifications: 

  • Understanding of CS basic 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
  • Basic knowledge of common machine learning techniques such as regression, clustering, and tree-based methods
  • Compelling desire to have a career in Artificial Intelligence/ Machine Learning and a strong passion for the subject
  • 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 AI and Machine Learning

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 the role. As part of the application process, individuals are required to submit responses to all components of the following  questions and responses will be reviewed for completeness as well as content. 

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. While working on your application responses, prioritize authenticity. Your genuine narrative, story, and experiences are essential for evaluating your candidacy and helps us understand your unique qualities within the candidate pool.

While LinkedIn profiles will not be reviewed in our hiring process, you must have a LinkedIn profile when applying in order for LinkedIn to receive your application through our applicant tracking system. In case you are new to LinkedIn or if you’d like some help in updating your profile, please visit this page or this video to see tips for creating a LinkedIn profile. 

 1. Your Personal Story and Impact

Please answer all parts listed below. We recommend your complete answer to this question be between 400 and 700 words.

a.    At LinkedIn, we strive for a culture that embraces and represents diverse ways of thinking, background, and approaches to solving the world’s problems. Tell us how your unique experiences and background shape the point of view that you will bring to LinkedIn. We are looking to understand your unique perspective, story, and background, along with how that influences the point of view you will bring to LinkedIn and your work in Artificial Intelligence / Machine Learning.

b.    We are looking for apprentices who are committed to reaching their goal of becoming an engineer.  Tell us how you have demonstrated continuous perseverance and tenacity to achieve a long-term goal or overcome challenges and setbacks throughout your life. This could include personal and professional experiences.

 

2. Your Journey into Artificial Intelligence/ Machine Learning

Please answer all parts listed below. We recommend your complete answer to this question be between 500 and 900 words.

a.    We recognize that there are many paths to Artificial Intelligence/ Machine Learning and we’d like you to walk us through yours. Tell us what sparked your interest in the subject and why you decided to explore that interest.

b.    How have you grown your skills independently or formally (consider personal projects, volunteer work, bootcamps, courses, or professional roles)? Tell us about the last technical topic you learned or are learning right now, and what your approach was. Beyond applying to this program, share how you plan to continue mastering machine learning and programming and how it fits into your long-term goals.

c.       What appeals to you specifically about the Artificial Intelligence/ Machine Learning  Apprentice Engineer role over the other REACH apprenticeship roles? We recommend you reference the position guidance to understand the role you are applying to. We are looking to understand how this interest has been demonstrated. Consider projects you have worked on, courses you have taken, prior positions you have enjoyed, etc.

 

3. Your Engineering Talent

Please answer all parts listed below. We recommend that your complete answer to this question be at least 400 words, but please use as many words as you need so that we fully understand your coding examples. In your answer, we would ideally like to see direct links to code you have written that you are most proud of, and that demonstrate your awesome ability. For example, you can send us a link to your Github project, but even better would be a link to files inside the Github project that shows off your skills! We also love demo sites, videos, and outside of the box thinking! Do not use formatting or hyperlinks. Include the full URL link to any media (YouTube, GitHub, Vimeo, etc.). 

If you cannot share a link to the code that you’ve written, please make sure to describe the project in detail and give us as much information as you can about the project. We will need to understand your project without seeing the code, so please help us to do that.   

 

At LinkedIn, every Artificial Intelligence/ Machine Learning engineer is responsible for both modeling and engineering work. Part of our evaluation process for this program is to understand your ability in both machine learning and programming. 

a.       Tell us about the machine learning project you are most proud of, whether it is one you completed in the past or are currently working on. Please share links to code you’ve written, a product or website you’ve built, an open-source project you’ve contributed to, and/or your favorite problem that you’ve solved. Where possible, please include independent or solo projects where we can see your direct contributions. If your examples include group work, please describe your individual contribution to the project. 
 
b.       In addition to your examples, please tell us what your objective was, what machine learning model, statistical model or embedding you trained, what results you achieved and the challenges along the way. Highlight how this coding work demonstrates your interest in this particular role.

 

4. Undergraduate Degree

Please state any undergraduate degrees you have completed. It is a requirement for this position to have an undergraduate degree and for the degree to be noted here for us to consider the basic qualifications for this position met.

 
  1. Review the job descriptions and application questions in the “Apprenticeship Roles- February 2025 Cohort” section (details will be posted on October 11th, 2024). Please identify the role(s) you feel are the best fit. While we invite you to apply to multiple roles, you can move forward with at most one role. We, therefore, advise you to only plan to apply for the roles you would want to be hired into, and for which you are qualified.

  2. Review the application questions for the positions you are interested in (posted in the role-specific pages) and draft your responses per the guidelines given.  

  3. Submit your application and essay responses between October 11th - October 15th at 11:59PM PT.

During the hiring process, candidates should expect the steps below:

Essay Application:

Our essay application process is designed to give individuals the opportunity to show us a range of qualities we believe will make them successful at LinkedIn. This includes their drive and ability to learn, tenacity and work ethic, unique perspective and passion for the role. As part of the essay application process, candidates are required to submit responses to all components of the four application essay questions. Responses will be reviewed for completeness as well as content. Candidates are expected to submit their responses by the application deadline (October 15th, 2024 at 11:59PM PT).

Take-home Project: 

A recruiter will contact you if you are selected for virtual interviews following initial application review. You will be asked to complete and submit an independent take-home project prior to the virtual interviews (mid November to late December).

Virtual Interview:

During the virtual interview, candidates will go through two interviews (one focused on technical skills and the other on soft skills) and a REACH Meet & Greet. In the technical interview, candidates will be expected to explain and extend their solution to the previously submitted take-home challenge. During the soft skill interview, a manager will get to know you beyond your technical skills (late November to mid January).

Offer: 

Candidates who receive an offer will find out more details about their future team and the program, including their minimum time in program based on their current experience and skill level (by late January).

Start date: 

There will be a set hiring date so that apprentices will start in groups and go through a custom REACH onboarding experience together. Your recruiter can provide further detail on this start date during the hiring process so that there is sufficient time to prepare (February).

Q: When is the next application period?   
A: We accept applications a few times a year, please check back early 2025. The dates will be posted on this site once confirmed.

Q: How many apprentices are you accepting?  
A: We expect to hire approximately 10-35 apprentices each cycle. Exact number of hires will depend on the program’s capacity as well as business need at the time.  
  
Q: What roles are you hiring for?  
A: Our available roles vary from cohort to cohort. Generally, we have encompassed roles such as Software Engineering (Backend, Frontend, Mobile, etc.), Data Science, Artificial Intelligence / Machine Learning, and other roles including User Experience Researcher, Technical Program Manager, and Cyber Security. To access the most up-to-date roles being offered, please refer to the "Apprentieship Roles- February 2025 Cohort" section.

Q: Is relocation offered?  
A:  Yes, relocation is offered. Our standard relocation policies and packages apply.  
  
Q: What office location will these roles be based in?  
A: 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 both 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. 

All roles within the February 2025 cohort offer a hybrid work arrangement. The majority of our hybrid teams are based out of our Mountain View, CA office. However, we also have teams located in our San Francisco office, and on occasion, our New York office. To find the precise office location for the track you are interested in, please visit the respective track-specific page.

Q: Will LinkedIn sponsor my visa?  
A: Apprentice roles are 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.  
  
Q: How is team placement determined?  
A: The program team will determine which team an individual joins, keeping in mind the apprentice’s interests. Team assignments will be based on several factors in order to set the individual up for success.  

Q: Are all applications reviewed?
A: Based on high volume of interest, we will not be able to review all applications. However, all applicants within this period will have an equal likelihood of review (i.e. applications will not be reviewed on a first come first serve basis).

Q: Do you need a LinkedIn profile in order to apply?
A: While LinkedIn profiles will not be reviewed in our hiring process, you must have a LinkedIn profile when applying in order for LinkedIn to receive your application through our applicant tracking system. In case you are new to LinkedIn or if you’d like some help in updating your profile, please visit this page or this video to see tips for creating a LinkedIn profile.