Meta Research Scientist Interview (process, questions, prep)

Research scientist interviews at Meta are really challenging. The questions are difficult, specific to Meta, and cover a wide range of topics.

The good news is that the right preparation can help you maximize your chances of landing a job as a Meta research scientist. 

To help you get there, we’ve gathered all the resources you need to perform well in your interviews: real candidate experiences from Glassdoor, insights from official Meta sources, and practical tips to help you move into each round with confidence.

Here's an overview of what we'll cover:

• Role and Salary
• Interview process and timeline
• Example questions
  • Coding questions 
  • System design questions
  • Role-related knowledge questions
  • Behavioral questions
• Interviewing tips
• Preparation plan

Let’s get started!

1. Meta research scientist role and salary↑

Before we cover your research scientist interviews at Meta, let's take a quick look at the role itself.

1.1 What does a Meta research scientist do?

Research scientists at Meta contribute to the advancement of AI, machine learning, and related technologies by conducting research, developing algorithms, and building systems that power Meta's products and infrastructure. 

The types of problems you work on will vary depending on your team. Based on reports from successful candidates, research scientist roles at Meta generally fall into three broad categories:

As you can imagine, this is a very hands-on, technical role. Research scientists—especially in AI and systems—are expected to write code and work closely with engineers to bring research into production. As you’ll see later in this guide, strong coding skills are a core part of the interview process.

While exact responsibilities vary by team, research scientists at Meta typically:

• Build machine learning models and optimization algorithms

• Design and analyze experiments to test new ideas and features

• Write code to support model deployment and system performance

• Develop tools and infrastructure to support research and production workflows

• Collaborate with product managers and engineers to define goals and ship features

Because Meta is a product-oriented company, research scientists are also expected to have strong product sense. At the end of the day, your role is to apply your technical and research expertise to build solutions that help Meta’s technologies perform and scale more effectively.

1.2 How much does a Meta research scientist make?

Research scientists at Meta are highly compensated. According to Glassdoor, they earn about 69% more than the average research scientist in the U.S.

Levels.fyi shows even higher pay for Meta research scientists (Facebook roles), with total compensation ranging from $305K (IC4) to $581K (IC6) in the US. Below are the average salaries by level:

The average salary of Meta research scientists also varies depending on location:

Location: Salaries are adjusted for cost of living. For example, a Meta research scientist at the IC4 level in the U.S. typically earns significantly more than an IC4 research scientist based in India.

Level: Both base salary and total compensation go up with each RS level.

While we presume that you already know which specific level you are applying for, it’s still good to double-check this with your recruiter. Your recruiter should be able to advise you on which level you’re being evaluated.

Ultimately, how you do in your interviews will help determine what you’ll be offered. That’s why hiring one of our ex-Meta interview coaches can provide such a significant return on investment.

And remember, compensation packages are always negotiable, even at Meta. So, if you do get an offer, don’t be afraid to ask for more. If you need help negotiating, use this salary negotiation guide and consider booking one of our salary negotiation coaches to get expert advice.

2. Meta research scientist interview process and timeline↑

2.1 What interviews to expect

What’s the Meta research scientist interview process and timeline? As mentioned in section 1.1, Meta research scientist roles typically fall into three main categories: software engineering–focused, data science–focused, and machine learning–focused. 

Because of this, the exact interview process may vary slightly depending on the role and team.

That said, most Meta research scientist interviews include a common set of question types, which we’ll cover in section 2.1.3. 

The process usually takes two to three months and includes the following steps:

• Resume screen
• Technical phone screen: 1 or 2 Leet-code style questions (45 minutes)
• Full Loop round: 3 or 4 interview rounds (45 minutes each)

Let's look at each of these steps in more detail below:

2.1.1 Resume screen

First, recruiters will look at your resume and assess if your experience matches the open position. This is the most competitive step in the process, as millions of candidates do not make it past this stage.

If you’re looking for expert feedback on your resume, you can get input from our team of ex-Meta recruiters, who will cover what achievements to focus on (or ignore), how to fine-tune your bullet points, and more.

It can also be helpful to get an employee referral to the Meta recruiting team internally. According to Glassdoor, 31% of candidates who got interviews with Meta were through employee referrals. So, if you do have a connection to someone who works at Meta, this can help you get your foot in the door for an interview.

2.1.2 Initial screen

In most cases, you'll start your interview process with Meta by talking to an HR recruiter on the phone. But don't underestimate this initial interview. For Meta research scientists, it’s a very focused technical round.

Candidates typically face one or two LeetCode-style questions, with 45 minutes to solve both. These questions often cover topics like arrays, graphs, dynamic programming, and strings. 

According to reports on Glassdoor, many of the problems are drawn from the top 150 most frequently tagged LeetCode questions, usually in the easy to medium difficulty range. 

Ultimately, this round is designed to test how comfortable you are with core algorithms and data structures under time pressure.

2.1.3 Full loop round

The final stage in the interview process for the research scientist candidate position is what Meta calls its Full Loop round of onsite or video conferencing interviews. 

As we’ve gathered from Glassdoor reports, this typically includes three or four interviews of 45 minutes each, consisting of:

• Behavioral interview 
• Coding interviews 
• System design interview
• Role-related knowledge interviews (statistics, research techniques)

For your coding interviews, you'll need to work through your solutions on a whiteboard or the online equivalent (like Codepad) if you're not there in person.

It's also worth mentioning that the questions you're asked in the Full Loop interviews tend to be more difficult than the questions from the initial screen. So be sure to double down on your preparation for them!

We'll further dive into each of these interviews in section 3.

3. Meta research scientist example questions↑

As mentioned earlier, the Meta research scientist interview process includes several types of interviews, depending on the role and specialization. In this section, we’ll walk through each one and give you a sense of the types of questions you’re likely to face.

The interviews are designed to evaluate your technical depth, coding ability, and how well you apply research in real-world contexts. Here's a quick overview of the main question types:

• Coding interviews, where you’ll solve two LeetCode-style problems per session. These are typically medium to hard in difficulty and more challenging than those asked during the initial screen.
• System design interviews, which focus on your ability to build scalable systems. Depending on the role, questions may range from traditional software system design to applied ML system design.
• Role-related knowledge interviews, which are tailored to your background. These may cover research methods, domain-specific technical questions (e.g., statistics or math), or include a discussion of a past project.
• Behavioral interviews, where you’ll be asked about past experiences, how you collaborate with others, and how you approach challenges.

In the sections below, we’ve included example questions reported on Glassdoor for each type of interview you can expect as a Meta research scientist. These are great example questions that you can use to start practicing for your interviews.

Let's dive right into it. 

3.1 Coding↑

The coding round is a core part of the Meta research scientist interview, especially for candidates in AI, ML, and systems-focused roles.

You’ll typically be asked to solve two LeetCode-style questions in each 45-minute session. The difficulty level is generally medium to hard, but be forewarned–some questions may look easy at first but require advanced or optimized solutions. 

The type of coding questions can vary depending on your role:

• For SWE and ML-focused roles, the questions are standard LeetCode-style algorithm problems—think arrays, trees, graphs, dynamic programming, and similar topics. The bar is high, and you're expected to solve both questions efficiently and with clean logic.
• For data science–oriented roles, like those in Central Applied Science (CAS), the coding round may involve exploratory data analysis (EDA). In this case, you will receive a dataset to analyze, build models, and suggest directions for further investigation.

One important note: You won’t be able to run your code during the interview. Meta uses a basic text editor with syntax highlighting, which means NO autocomplete, NO AI tools, and NO code execution.

Interviewers are forgiving of small syntax errors but will expect you to understand core algorithms and functions well enough to write correct logic without needing to test it.

To prepare, many candidates recommend using LeetCode Premium. Meta tends to pull from the same question bank, so filtering Meta-tagged questions from the past three months and sorting them by decreasing frequency will give you a really solid list of questions to study.

Here are some example coding questions you can practice with. If you want more, check out our list of Meta coding interview questions (with links to solutions). 

3.2 System design↑

This 45-minute interview focuses on your ability to design scalable systems. The goal is to show how you break down a product or research problem and use your existing tools and knowledge to build a practical, scalable solution.

Again, the structure and style of the system design interview will depend on the role:

• SWE-focused roles tend to follow traditional software engineering system design formats. You may be asked to design large-scale applications like “Design Yelp” or “Design a web crawler,” focusing on components, architecture, and performance.
• Data science–oriented roles often focus on ML systems design. These questions are more applied and closer to modeling user behavior. For example: How would you build a system to suggest related questions on a site like StackOverflow?
• AI/ML-focused roles follow a similar format to CAS interviews but may be more tailored to the work of the team you're interviewing with. Expect questions that walk through how you’d handle data pipelines, model training, deployment, and monitoring in a real product context.

Across all tracks, interviewers are looking for clear reasoning, well-structured thinking, and awareness of trade-offs. You’ll be expected to talk through components, identify bottlenecks, and explain how your system will scale with real-world demands.

Let’s look at some practice questions. 

Check out our full Meta system design interview guide for more tips and strategies. And if relevant, you can also practice with this list of machine learning system design exercises. 

3.3 Role-Related Knowledge↑

For the role-related knowledge interview, you will be assessed on how well your background aligns with the specific needs of the team. This round focuses on your domain expertise, research experience, and ability to apply technical concepts in context.

Depending on your specialization, this could include:

• Research presentations, where you're asked to present a paper you've written or a recent project. For data science–oriented roles, this is a chance to walk through your methodology, findings, and the reasoning behind your choices.
• In-domain technical questions, which typically cover topics like statistics, probability, or applied math. These may include concept checks (e.g., explaining Bayes’ Theorem) or open-ended questions that require you to reason through which statistical methods apply in a given scenario.

While correctness is the priority in this round, communication matters, too. You’ll need to explain technical ideas in a way that shows depth of understanding and practical relevance.

3.4 Behavioral↑

In addition to the question types outlined above, you can also expect to be asked some behavioral or “resume” questions about your past work, how you handle challenges, and why you're interested in Meta.

For research scientist roles, this interview is typically conducted by someone with a PhD, often a fellow research scientist. Interviewers tend to focus more on your research background, how you approach problems, and how well your past work fits the team’s goals.

Behavioral interviews at Meta can be tricky. There’s no clear-cut “correct” answer, which makes it harder to gauge your performance in the moment. 

That said, this round carries significant weight in the hiring decision. Meta is looking for thoughtful, self-aware candidates who can navigate ambiguity, communicate clearly, and work well across teams.

Below are some behavioral questions reported by research scientist candidates on Glassdoor. 

You can also check out our Meta behavioral interview guide to learn how to give strong answers to behavioral questions, along with example questions to practice with.

4. Meta research scientist interviewing tips↑

You might be a fantastic research scientist, but unfortunately, that won’t necessarily be enough to ace your interviews at Meta. Interviewing is a skill in itself that you need to learn.

Let’s look at some key tips to make sure you approach your interviews in the right way.  

4.1 Learn a technique for answering questions

When answering your Meta RS interview questions, you should focus on your most relevant achievements and experiences and communicate them in a clear way. An easy way to achieve this is to use a step-by-step method to tell your stories. 

The STAR method (Situation, Task, Action, Result) is a popular approach for answering behavioral questions because it’s easy to remember. You may have already heard of it. 

However, we’ve found that candidates often find it difficult to distinguish the difference between steps two and three or task and action. Some also forget to include lessons learned in the results step, which is especially crucial when discussing past failures.

So, we’ve developed the IGotAnOffer method (SPSIL: Situation-Problem-Solution-Impact-Lessons) to correct some of the pitfalls we’ve observed when using the STAR method.

4.2 Get used to setting up the situation in 30 seconds or less

Whether you’re using the SPSIL or STAR method to answer behavioral questions, use a timer while you practice to ensure you provide only the necessary information. Spending too much time on setting up the situation is one of the most common mistakes candidates make.

4.3 Ask clarifying questions

Often the questions you’ll be asked will be quite ambiguous, so make sure you ask questions that can help you clarify and understand the problem. Most of the questions will focus on testing your technical proficiency.

4.4 Be conversational

Meta wants to know if you have excellent communication skills. So make sure you approach the interview like a conversation. 

Meta will also be testing you on your ability to tell a clear and concise story through data, especially to stakeholders who may or may not have a technical background. So be sure to brush up on your basics and practice interpreting them in a way that’s clear and easy for everyone to understand.

4.5 State and check assumptions

You need to explicitly state assumptions, explain why you’re making them, and check with your interviewer to see if those assumptions are reasonable.

4.6 Adapt to follow-up questions

Don’t be alarmed if your interviewer asks follow-up questions; this is perfectly normal. Listen carefully to the way your interviewer is asking these questions, as there will often be a subtle clue about the specific skills they’re looking to assess from the next part of your answer.

4.7 Be honest and authentic

Be genuine in your responses. Meta interviewers appreciate authenticity and honesty. If you faced challenges or setbacks, discuss how you improved and learned from them. When talking about failure, don’t try to hide your mistakes or frame a weakness as a strength. Instead, show what you learned and how the failure helped you grow.

4.8 Get comfortable visualizing your system design process

During your technical design interview, your interviewers will want you to visualize your answer. Practice describing a past project that’s relevant to Meta by organizing it with block diagrams on a whiteboard. What your interviewers will be looking out for is how you approach a problem in a way that’s both structured and creative.

4.9 Center on Meta’s values

Familiarize yourself with Meta’s culture and core values and align your behavioral responses with them. Meta values certain attributes such as passion for technology, collaboration, and focus on the user.

5. Preparation Plan↑

Now that you know what questions to expect, let's focus on how to prepare. It's no secret that the performance bar at Meta is high. Some people even go as far as quitting their jobs to prepare for interviews full-time. This is obviously extreme and not what we recommend doing, but it shows how much effort some candidates are ready to put in.

We've coached more than 15,000 people for interviews since 2018. Below is our four-step prep plan for Meta. 

5.1 Learn about Meta’s culture

Most candidates fail to do this. But before investing tens of hours preparing for an interview at Meta, you should take some time to make sure it's actually the right company for you.

Meta is prestigious, and it's, therefore, tempting to ignore that step completely. But in our experience, the prestige in itself won't make you happy day-to-day. It's the type of work and the people you work with that will.

If you know engineers who work at Meta or used to work there, it's a good idea to talk to them to understand what the culture is like. In addition, we would recommend reading the following:

1. About Meta
2. Meta’s mission statement
3. Meta's 6 core values 
4. Meta’s products
5. Meta Newsroom
6. Meta Careers
7. Meta Life
8. Meta Diversity
9. Meta Employee Benefits
10. Interviewing at Meta blog
11. How to get users and grow (by Alex Schultz, VP of Growth at Meta)
12. How Facebook Used Science And Empathy To Reach Two Billion Users (by FastCompany)

In addition, we would recommend reading the following:

13. Facebook’s hacker culture (by Mark Zuckerberg, via Wired)
14. Meta annual reports and strategy presentations (by Meta)
15. Meta's approach to tech trends (by CB Insights)
16. Meta.org culture analysis (by Panmore Institute)

5.2 Practice by yourself

As we've outlined above, you'll have to prepare for several different categories of questions ahead of your Meta research scientist interviews.

In this article, we've recommended various deep-dive articles that will help you prepare for each question category. Here's the complete list, plus a couple extras we think could be useful.

• Official Meta guides: Meta’s Full Loop Interview Guide
• Coding
  • General: Coding interview prep
  • Meta-specific: Meta coding interview questions
  • Topic-specific: arrays, graphs, dynamic programming, and strings

• In-domain technical (statistics, experimentation, data analysis)
  • How Experimentation Informs Product Development – LinkedIn
  • The Pitfalls of A/B Testing in Social Networks
  • Khan Academy – Statistics & Probability Course
  • Brilliant.org – Courses on Statistical Probability & Applied Math (some free, others paid)
  • StackExchange – Search Q&As on statistics, machine learning, experimentation
• System design: System design fundamentals, Meta system design interview, ML system design exercises

• Behavioral questions
  • People management: People management questions in tech interviews
  • Collaboration and Partnerships: Dealing with conflict, dealing with stakeholders
  • General: Meta behavioral interview questions
• Career conversation & motivation: "Why Meta?" interview question, Common behavioral questions in engineering interviews
• General: Most-asked Meta interview questions

Once you’re in command of the subject matter, you’ll want to practice answering questions. But by yourself, you can’t simulate thinking on your feet or the pressure of performing in front of a stranger. Plus, there are no unexpected follow-up questions and no feedback.

That’s why many candidates try to practice with friends or peers.

5.3 Practice with peers

If you have friends or peers who can do mock interviews with you, that's an option worth trying. It’s free, but be warned, you may come up against the following problems:

• It’s hard to know if the feedback you get is accurate
• They’re unlikely to have insider knowledge of interviews at your target company
• On peer platforms, people often waste your time by not showing up

For those reasons, many candidates skip peer mock interviews and go straight to mock interviews with an expert. 

5.4 Practice with experienced ex-Meta interviewers

In our experience, practicing real interviews with experts who can give you company-specific feedback makes a huge difference.

Find a Meta interview coach so you can:

• Test yourself under real interview conditions
• Get accurate feedback from a real expert
• Build your confidence
• Get company-specific insights
• Learn how to tell the right stories, better.
• Save time by focusing your preparation

Landing a job at a big tech company often results in a $50,000 per year or more increase in total compensation. In our experience, three or four coaching sessions worth ~$500 will make a significant difference in your ability to land the job. That’s an ROI of 100x!

Click here to book research scientist mock interviews with experienced Meta interviewers.