Get a Job at Meta: Interview Process and Top Questions

Would you like to work at Meta, one of the biggest tech companies in the world?

Meta’s mission is to connect the world. It has built massively successful products that you probably use daily, such as:

• Social media platforms Facebook, Instagram, and Threads
• Virtual reality (VR) hardware and software, including Oculus (now rebranded as Quest)
• Communication applications like Messenger and WhatsApp

Operating and innovating products used by billions of users takes a large and dedicated team of product and business people, software and machine learning engineers, data scientists, and others.

If you’re interested in joining the Meta team, you’ll face several rounds of challenging interviews.

The Meta acceptance rate may be as low as 5%.

Below, we’ll break down the Meta interview process and help you prepare for the most commonly asked questions for different roles. 

Check out these popular role-specific guides for jobs at Meta:

• Meta Engineering Manager Interview Guide
• Meta Software Engineering Interview Guide
• Meta Product Manager Interview Guide
• Meta Machine Learning Interview Guide

What is the Meta interview process?

Meta interviews can take anywhere from four weeks to two months and involve:

• A screening call with a recruiter,
• A domain-specific screening call,
• A full loop with a mix of domain-specific and behavioral rounds.

Meta is invested in many technologies poised to shape the future, and their company culture page reflects this. You can search for open roles by technology including:

• Generative AI
• Artificial Intelligence
• AR/VR
• Machine Learning
• Infrastructure
• Software Engineering

The careers page is more granular.

Search for open roles in product, business, engineering, data, and others.

Meta prides itself on hiring talented people who can learn and adapt rather than just domain experts. They value the unique perspective you bring as an individual and encourage authenticity in interviews. 

The company is known for being relatively flat as opposed to hierarchical, so you’re likely to be interviewed by a mix of peers, higher-ups, and cross-functional partners. 

Step 1: Recruiter phone screen

The first step is a 30-minute phone call with a recruiter.

This first screen looks similar for all roles – recruiters want to confirm your basic qualifications and culture fit. 

You’ll be asked light behavioral questions on your background, professional experience, projects, and any accomplishments. Expect questions like:

• Why Meta?
• Tell me about yourself.
• What’s an obstacle you’ve overcome? 

Read some of these career stories from Meta’s Careers blog to get a sense of how to do this. For example,

• Sophia, an engineering director, shares how embracing her authentic self helped her succeed.
• Michael, a former pro basketball player and machine learning engineer shares his path to Meta.
• Tzach, a product manager, shares what it’s like to transition from the startup world to Facebook. 

After answering some behavioral questions, you’ll have a chance to discuss the role and responsibilities you’d be taking on and to ask any questions about the rest of the interview loop. 

Step 2: Job-Skills Screen

For technical roles like data science, machine learning engineering, or software engineering, this screen will focus on your technical skills.

For product / business roles, the screen will assess your product design and analytical thinking skills. Technical Screen for Engineering roles 

Engineering candidates (both software engineers and machine learning engineers) will be assessed on their ability to solve coding challenges.

You’ll spend the first few minutes making introductions and answering one or two questions about your resume, but the bulk of the 45-minute interview will be spent solving coding questions involving data structures, algorithms, recursions, and binary trees. 

Coding questions are asked virtually through a platform like CoderPad, where your interviewer can see your work.

You’re expected to explain your thinking and justify your approach as you code. Interviewers might jump in with additional questions, additional challenges, or ask you how you’d optimize your solution. 

Meta is looking for:

• Communication skills.
• Ability to break down and solve problems.
• Ability to write clean, efficient code.
• Ability to verify your solutions by testing edge cases.

Technical Screen for Data Roles 

The technical screen for data scientists runs around 45 minutes and focuses on these key skills:

• Programming: Perform basic data manipulations such as merging datasets, filtering, and cleaning data using any type of SQL you prefer.
• Research or experimental design: Identify and design scientific testing, eliminate irrelevant variables, and establish relationships between relevant variables. 
• Metrics: Identify the right suite of metrics to measure success or inform on progress for a variety of real-world business scenarios. 
• Data analysis: Answer questions on descriptive statistics, measurement models, exploratory data analysis, and other basic data analysis topics.

Example questions include:

• Programming: Write a SQL query to remove duplicate emails from a users table.
• Research or experimental design: Identify success metrics for a marketing campaign to get new users, then design an experiment to determine if the campaign should continue
• Metrics: Why do you think Meta invested in workplace chat? How would you set goals and measure the success of this product? 
• Data analysis: What does confidence level mean when building a confidence interval?

Meta is looking for candidates with skills and experience that will help it achieve its vision of connecting the world, but it’s okay to say “I don’t know.” Identifying gaps in your knowledge and figuring out how to work around them is a powerful skill in itself, as you’ll often face problems you’ve never seen before at Meta. Interviewers are looking for candidates who can roll with ambiguity. 

Product Sense and Analytics Screen for Product Roles

Product managers will be tested on their product sense and analytical thinking skills during the 45-minute screening interview. 

The product sense question is formatted as a hypothetical case question.

You might be asked to describe a product you think is great and why, or you might be given a scenario and asked what you would do as a PM or CEO of the company. 

An example product sense question is “How would you disrupt the travel industry?”

Analytical questions are formatted similarly. You’ll be given a situation and asked to identify and prioritize opportunities, build a plan of action, and how you’d execute it. The question may be vague, but you will be expected to give a set of metrics you’d track to measure success.

An example analytics question is “Let’s say you are the PM of Messenger, and you noticed that its DAU has gone down significantly. How would you go about looking for the root cause?”

Meta is looking for: 

• Strong critical thinking skills.
• Ability to prioritize and make difficult tradeoffs.
• Ability to adapt to change.

Step 3: The Full Loop 

Once you pass the recruiter and screening interviews, you’ll be scheduled for a full loop. For most roles, the full loop consists of about 5 rounds roughly broken down into three categories – coding, design, and behavioral

Coding Interviews

Most interviewees get two coding interviews lasting 45 minutes each. Similar to the technical screen, you’ll solve each coding challenge live through an online collaborator app. 

Solving these challenges in the time allotted with optimal space-time complexity can take a lot of practice.

You should aim to solve medium difficulty coding questions in 35 minutes and practice plenty hard questions (as interviewers will try to find your limits.)

Besides getting plenty of practice, studying data structures and algorithms is key. 

Design Interviews

Next is the design round. These questions are much more vague and open-ended.

Interviewers are trying to get a sense of how you deal with ambiguity and break problems down into addressable chunks. 

Engineers will be asked system design questions such as “Design Facebook Newsfeed” while product roles will be asked product design questions like “Design a better doctor search and visit experience.”

System design questions probe candidates’ knowledge of system design principles and how to scale a complex system according to anticipated traffic patterns.

Candidates are expected to justify their technical decisions, consider tradeoffs, and talk through important edge cases as they arrive at their final answer. 

Product design questions assess a candidate’s ability to understand and empathize with end users, identify pain points, and design efficient solutions that align with business objectives. 

Experimental design questions for data roles center around the ability to design scientifically valid, efficient, and interpretable experiments. 

Behavioral Interviews

You’ll probably face at least two coding and design interviews each, but you’ll go through only one behavioral interview.

Like the others, it lasts for around 45 minutes, and it is much more conversational and open-ended than the others. 

Behavioral questions at Meta assess your leadership and drive. Meta is looking for candidates who are both leaders and team players. Because the company is so collaborative, behavioral questions often center around how you work on cross-functional teams. 

At Meta, cross-functional teams consist of engineers, product managers, designers, data scientists, and more. Each member of a team needs to be able to communicate with others and align on common goals while making sure that all important perspectives are considered. 

Expect many questions on how you’ve contributed to cross-functional teams in the past. Be prepared to discuss your successes and failures, the lessons you’ve learned, how you resolve conflict, and how your experiences have shaped your perspective as a professional. 

Step 4: Evaluation and Hiring Decision

Congratulations! You’ve made it through your full loop at Meta.

The candidate evaluation and eventual decision consist of 4 stages – a recruiter debrief, candidate review meetings, a hiring committee review, and, finally, an offer. 

After your full loop, your recruiter will gather feedback from interviewers and debrief.

If you’ve done well, they will collect your resume, interview scores, referrals, and any other relevant information, and put together a packet to be passed on to the candidate review meeting. 

The candidate review meeting is held by the team leaders and hiring manager(s) for the team you’re applying for and will review the pool of applicants that have passed the recruiter debrief.

They will select the candidate they recommend for hire, and pass that applicant’s information along to the hiring committee.

The hiring committee is separate from the team making the hiring recommendation and consists of senior executives whose job it is to make final hiring decisions.

They ensure that Meta hires only the best-fit candidates. If the hiring committee wants to recommend a candidate, that candidate packet is sent to a VP for final sign-off.

Most often, the committee and the VP go with the hiring team’s recommendations. If you are selected, you will receive an offer. At that point, you can negotiate your salary and other benefits.

If you aren’t extended an offer, you should receive some basic feedback on why you didn’t make it. 

What are the top Meta interview questions?

Here is a list of the top Meta interview questions candidates have been asked recently. 

Coding

Engineers will get standard coding challenges with an emphasis on data structures and algorithms. For example: 

• Given a matrix, find the number of 1s in a given submatrix.
• Give the maximum sum of a contiguous subarray of size k in an array of size n.
• Imagine an array of numbers where every number occurs twice. However, one number appears only once. How would you find this number in O (log n) time? 
• Reverse a linked list.
• Given a collection of intervals, merge all overlapping intervals. 
• Take the square of a sorted array.

Data analysts, product analysts, and data scientists will get SQL coding questions, such as:

• You are building a naive recommender. Given sample tables, write a SQL query to create a metric to recommend pages for each user based on recommendations from pages their friends have already liked.
• Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. 
• Given a table that represents search results from Facebook searches. Write a query to compute a metric to measure the quality of search results for each query. 

System Design

• Design live commenting for Facebook.
• Design a web crawler.
• Design Facebook Newsfeed.
• Design Facebook Messenger.
• Design an Amazon price tracker like CamelCamelCamel.

Product Design

• What’s your favorite product and why?
• Imagine you’re a PM for Meta. Design a product for volunteering. 
• How would you design parking features on Google Maps?
• How would you improve Instagram Stories?
• Imagine you’re a PM for Meta. Design a product for musicians.

Experimental Design

Explain how you would set up a randomized controlled trial (RCT) to evaluate the effectiveness of a new privacy feature on Meta's messaging platform.

• Describe a methodological approach you would use to assess the usability of a new user interface design for Meta's virtual reality applications.
• What data sources would you leverage to evaluate the effectiveness of Meta's educational initiatives?
• How would you recruit participants for interviews or focus groups, and what strategies would you use to ensure diverse perspectives are represented?
• Can you explain how you would analyze the data to identify patterns and insights regarding ad targeting effectiveness?

Analytics

• As a PM at Meta, why is it critical to address ads that violate community guidelines and regulations? What metrics would you use to track success in this area?
• As the PM at Netflix, after launching Netflix podcasts 6 months ago, how would you define and measure the success of this initiative?
• Meta’s office complex in Menlo Park has two modes of transit: a bus route and an Uber-style rideshare. The company wants to eliminate one of these options. What metrics would you use to make this choice?
• Imagine you’re a PM for Trader Joe’s. Sales are declining at stores where Instacart and Blue Apron are also active. What would you do?
• Imagine you’re a PM for Meta. How would you measure the success of Facebook’s notification bell and its drop-down menu?

Behavioral

• Give an example of a time when you dealt with a difficult stakeholder.
• Tell us about a time when you disagreed with a manager.
• Tell me about your most significant accomplishment. 
• What is the most innovative project you worked on?
• Walk us through a time when you proactively investigated and resolved a sensitive or complex issue.
• How do you prioritize and manage projects while coordinating with global cross-functional partners?

Meta’s Interview Loops Explained

Meta is transparent about looking for candidates who work well cross-functionally, take the initiative to solve problems proactively, and have the ability to prioritize and execute the most important tasks.

Behavioral

Most candidates will get behavioral questions assessing their leadership, drive, and ability to work cross-functionally.

To ace behavioral questions, you should first familiarize yourself with Meta’s core values:

“At Meta, everything we do is about helping people feel connected and closer. It’s in our technologies, our mission, and how we collaborate. Working collectively and valuing each person for the differences we bring allows us all to do more. The pace is fast and the challenges are enormous, but this is how we thrive.” - Meta Careers

• Move fast: We build and learn faster than anyone else. Acting with urgency, we don’t wait until next week to do something we could do today. We continuously work to speed up our highest-priority initiatives by methodically removing barriers that get in the way. It’s about moving fast in one direction together–as a company and as individuals.
• Focus on long-term impact: We emphasize long-term thinking that encourages us to extend the timeline for the impact we have, rather than optimizing for near-term wins. We should take on the challenges that will be the most impactful, even if the full results won’t be seen for years.
• Build awesome things: We push ourselves to ship things that are not just good, but also awe-inspiring. We’ve already built products that are useful to billions of people. In our next chapter, we’ll focus more on inspiring them as well, in everything we do.
• Live in the future: Let’s build the future of work that we want, with an in-person focus designed to support a strong, valuable experience for our people who have chosen to work from the office and a thoughtful and intentional approach to where we invest in remote work. This also means being early adopters of the future products we build to help people feel present together wherever they are.
• Be direct and respect your colleagues: We create a culture where we are straightforward and willing to have hard conversations with each other. At the same time, we are also respectful and when we share feedback, we recognize that many of the world’s leading experts work here.
• Meta, metamates, and me: We are stewards of our company and our mission. We have a sense of responsibility for our collective success and to each other as teammates. It’s about taking care of our company and each other.

Every behavioral answer you give should align with one or more of these core values.

Meta recommends that candidates use the STAR framework (Situation, Task, Action, Result) format to keep behavioral answers tight, but they also want to see the authentic you. Interviewees want to see that you:

• Drive resourcefulness and results.
• Seek opportunities to learn and grow.
• Take ownership and accountability.
• Resolve conflict.

As you practice answering behavioral questions, ask yourself whether your answers:

• Demonstrate initiative.
• Exhibit introspection and self-awareness.
• Showcase your ability to be open and learn from mistakes.
• Demonstrate leadership qualities like conflict management and empathy.

Design 

Product, data, and engineering roles will all have to design things during their day-to-day.

Design skills are tested in the full loop, and for some roles, in the screening calls.

Engineers will face system design interviews.

System design interviews cover all aspects of a deeply technical design, including product ideas, usability, scalability, and the technologies used to build a holistic software solution. 

Interviewers want to see engineers architect a solution to a high-level problem without forgetting crucial details. They are assessing your:

• Problem navigation: Can you break down a problem and organize it? Can you recognize the constraints and identify potential solutions?
• Solution design: Can you work towards a solution that addresses the critical aspects of the problem while ignoring unimportant details?
• Technical excellence: Can you dive deep when needed? Can you identify important dependencies and trade-offs?
• Technical communication: Can you articulate your ideas clearly, take direction and feedback, and build? 

Here are some tips for acing system design rounds:

• Study design patterns for software systems that you use, especially Meta’s. How do those patterns apply to the problem space you’ve been given? How would you design it from scratch?
• Avoid jumping straight to optimal solutions. Start simple, think through tradeoffs, and improve as you go. 
• Read company engineering blogs to learn about different approaches that have worked (or failed) in the real world and why.
• Practice zooming in and out on the details of a system design challenge. Repeatedly go back to business objectives when stuck. What are you trying to do and why?

Product roles will face product design challenges.

Interviewers want to see end-user empathy, business savvy, creative problem-solution, and prioritization and execution skills. Be sure to hit these core focus areas while you’re creating your design:

• Understand the product landscape and business motivation for whatever you’re designing.
• Show you can determine the right target audience.
• Identify and prioritize the right problem(s).
• Develop creative and impactful solutions.
• Make intentional and logical design choices.

As you practice product design questions, be sure you are demonstrating:

• How you take an ambiguous idea and create a great product.
• Your ability to empathize with the user.
• Your intentional design choices.
• How you prioritize and get things done.
• How you create goals and handle different constraints to the product.

Data roles will face experimental design questions to assess their ability to design efficient and scientifically sound experiments that will result in easy-to-interpret, actionable results.

To ace experimental design questions, review basic statistics, probability theory, and research design principles. Practice asking yourself how you would test and analyze certain things in your daily life and in the products you use. Be sure to practice establishing relationships between the right variables when you have a business question in mind. As you practice, ask yourself:

• How would I design an experiment to prove / disprove this?
• If an experiment won’t work, what’s an alternative?
• What are the downsides of the methodology I want to use?
• Are there any biases in the experiment or my analysis that I should correct for? 

Coding

Software engineers, machine learning engineers, engineering managers, infrastructure engineers – all technical roles will face coding challenges in multiple rounds.

Although these coding challenges don’t translate well to the real work of engineering, they are straightforward to study and prepare for. Recall that Meta is looking for:

• Communication skills.
• Ability to break down and solve problems.
• Ability to write clean, efficient code.
• Ability to verify your solutions by testing edge cases.

Note that product or system generalist candidates can choose to code in whatever language they like, while UI or frontend engineers will be expected to code in JavaScript.

Here are some useful tips for acing coding challenges at Meta:

• Schedule study and practice time daily. It’s easier to do 30 minutes a day than to cram for 48 hours right before your interview. Most candidates spend a lot of time practicing coding challenges with peers in mock interviews, so don’t neglect this step. You’ll need to practice writing code without a compiler or a debugger, so try your hand at solving coding challenges in a simplified environment.
• Study a wide variety of problems rather than going deep in a specific area. You never know what you’re going to get!
• Practice with a wide variety of algorithms and data structures. Meta doesn’t ask dynamic programming questions, so you can skip those - but don’t neglect basic data structures like arrays, stacks and queues, hash tables, trees, graphs, and heaps, and study iteration, sorting, divide-and-conquer, and recursion.
• Practice timing yourself while you talk through your answer. This is probably very different from how you’re used to working, so get comfortable. 

Interview tips

What should you know before going into a Meta interview?

Meta wants you to do well.

Meta recruiters are known to be helpful and flexible and will share in-depth interview preparation guides with you before you enter the full loop. If you’re interviewing for a more junior role, you’ll have the opportunity to book a mock coding interview with a Meta engineer. You can find many inspiring and helpful blogs, videos, and guides on Meta’s careers page. 

Meta looks for employees who can work well cross-functionally.

Cross-functional teams of engineers, product managers, designers, and data roles are essential to Meta’s success. Notice that many of Meta’s core values speak to the importance of collaboration. Your cross-functional collaboration skills will be assessed throughout the whole interview experience, so begin preparing your stories now. 

It’s okay to say “I don’t know.”

Meta isn’t necessarily looking for domain experts. You should be competent enough to do the job you’re interviewing for, but the company acknowledges that no one knows everything. If you get stuck, feel free to say “I don’t know” – but follow that up with “Here’s how I would go about finding out” or “Here’s an alternative solution.”

Study Meta’s core products.

Not all companies will ask design questions on their products, but Meta does. Download Instagram, WhatsApp, and/or Messenger, and get a sense of the experience so that you have intelligent answers prepared in case you’re asked what you think about these products, or how you’d improve them.Meta’s many different blogs are also great resources to learn about the infrastructure behind these products and how they work. 

Get a referral from a Meta employee

Meta is one of the biggest tech companies in the world. A great way to increase your visibility is to get a referral from a Meta employee.

FAQs

How hard are Meta’s technical interviews?

Meta’s technical interviews are known to be challenging. For coding rounds, you should aim to solve medium and hard problems in about 35 minutes. For design interviews, you should aim to solve them in roughly the same amount of time, including discussions around scalability, risk mitigation, and any important edge cases. That said, Meta doesn’t expect you to know everything or be perfect. They’re looking for candidates who can lean into ambiguity and get the job done when faced with obstacles. 

How long does it take to hear back after interviews?

Meta recruiters are known to be fairly responsive. You can expect to hear back with a final answer within a week or two after the full loop interview, but if you haven’t heard back in that time, reach out to your recruiter. 

What is Meta’s cooling-off period for interviews? 

There is no cooling-off period if you apply for a different role. Some teams will ask you to wait a year, mainly to give yourself time to improve your skills and do more interview preparation. Most people suggest waiting three to six months before re-applying to Meta regardless of the role. 

More interview prep resources

• Practice answering the most common Meta interview questions.
• Read through our Meta interview guides.
• Book a 1:1 coaching session with a Meta interview coach.
• Book a mock interview.
• Explore interview prep courses for product management, engineering, data science, and many other roles