Reddit Machine Learning Engineer (MLE) Interview Guide

tl;dr

Reddit is a link aggregator and social media sharing site. With more than 97 million daily unique visitors, it’s one of the world’s top-ten most visited websites (as of 2025). Reddit serves as the bulletin board and forum for a staggering number of communities (known as subreddits) that collectively cover almost every topic and interest imaginable. Over 100,000 subreddits already exist, and more are created every day.

Even though Reddit operates at massive scale, its work culture still embodies the flexibility, individual impact, and tight-knit atmosphere of a much smaller startup. Reddit’s ML engineering teams tend to be comparatively small and lean, so ICs have the opportunity to wear a few different hats and take their own initiative on how to tackle their projects. Employees also have flexible work-from-home and hybrid options. You might be inclined to come into the office anyway, however! Reddit staff report that their coworkers are warm, friendly, and eager to share their knowledge. There are plenty of social events, coffee chats, and lively Slack discussions to go around.

What does a Reddit Machine Learning Engineer do?

Reddit’s ML engineers usually specialize in a particular product area. For example, they might focus on improving Reddit’s “search” and “recommendation” features by using ML tools to identify the most relevant or useful related content. Or, they might build out a feature that uses language models to interpret, analyze, and/or generate natural language text.

Many ML engineers at Reddit are dedicated to optimizing its systems for advertising and sponsored content, which is the company’s largest source of revenue. Reddit users are ripe for narrowly targeted advertising, based on traits like their subreddit memberships and voting behavior, and the trends and network effects that proliferate across the site can be valuable for marketers that jump on the bandwagon at the right time. If you become an ML engineer on the Reddit Ads team, you’ll develop ML tools that analyze this rich corpus of data and identify the most profitable opportunities for sponsored content.

To give you an approximation (ML roles are likely paid similarly though slightly higher than SWE roles), the average total compensation across software engineering levels at Reddit are:

• IC1 (entry-level): $145k
• IC2: $205k
• IC3: $270k
• IC4 (Senior): $391k
• IC5 (Staff): $431k
• IC6 (Principal): $890k

Before you apply

• Refresh your knowledge of machine learning algorithms and systems, including how they perform in real-world situations.
• Read Reddit’s engineering tech blog, which is hosted on its own subreddit: /r/RedditEng to learn about some of the projects you might work on and to prepare for the system design round.
• Practice for the coding challenges by completing problem sets from Kaggle (for ML tasks) and by studying ML questions.

Interview process

Applicants to Reddit go through 3-4 interview stages before they get hired. The first is a phone screen with a recruiter; sometimes there’s an additional call with a hiring manager. After that comes a technical screen that tests your ML coding skills and knowledge. The final stage is a lengthy interview loop divided into four sections: “ML fundamentals” (i.e., conceptual knowledge), coding, ML system design, and a Q&A with the hiring manager.

Although this sequence of steps is pretty consistent across MLE positions at Reddit, their exact content and format is largely up to the specific team and hiring manager attached to the role.

1. Recruiter Screen

The first step is usually a brief call with a recruiter, discussing basic aspects of the role. This call covers topics like your background, details about the position itself, and the upcoming interview process. Unlike most tech companies, Reddit’s recruiters might also ask you a technical question or two.

Although it’s not common, it’s possible you’ll get an additional call scheduled with the hiring manager. If so, expect the hiring manager to ask deeper questions about your skills and experience, particularly when it comes to projects using ML. They will also use this call to describe the role and their team in greater detail, making it an excellent chance for you to ask your own questions about what working with them will be like.

Sample questions include:

• Tell me about yourself.
• Why do you want to work at Reddit?
• What are you looking for in your next role?
• What are your salary and equity expectations?
• Explain overfitting.

2. Technical Screen

The technical screen can take a few different forms depending on the team, but most commonly you’ll be asked to solve an ML coding problem via an environment like CodeSignal. A typical problem will present you with a goal and a set of data, and your task will be to come up with a machine learning implementation to achieve that goal. (For a concrete example, think of the classic Kaggle problem that provides mortality and demographic data for the Titanic’s passengers, and asks you to build a model to predict who survived.)

There’s a good chance you’ll be given a problem that relates to a Reddit product concern, such as content ranking or fraud detection. You’re especially likely to get a domain-targeted question if the role calls for a narrow specialty of ML, like computer vision. Nonetheless, you shouldn’t rule out a more generic ML question, or in rare cases, even Leetcode-style problems.

The tech screen focuses primarily on coding skills, but there will also be a short set of technical questions at the end.

Sample problems include:

• Write a binary classifier to detect fraudulent posts.
• Predict how long a new DoorDash order will take based on data from previous trips.
• Implement the K-nearest neighbors algorithm.

Print all combinations of numbers from 1 to n that sum to n.

Asked at Adobe, Apple, LinkedIn + 2 more 

View 2 answers

3. Final round

The last stage of the interview process is a virtual on-site consisting of four rounds of one hour each. One is a Q&A session that evaluates your knowledge of machine learning fundamentals. You will also have at least one round dedicated to hands-on coding, similar to the first tech screen. For some roles, particularly junior ones, you might have two coding rounds, but more often, the third round will test your knowledge of ML system design. Lastly, you’ll sit down to an interview with the role’s hiring manager, discussing your skills and experience and how you’ll fit into the team.

ML fundamentals

In this round, the interviewer will test your knowledge of specialized machine learning topics. Interviewers at Reddit have free rein to ask whatever questions they feel are appropriate, so expect an open-ended session of questioning that covers a wide breadth and depth of subjects.

For example, you might get academic questions about the mathematical and statistical underpinnings of ML that are somewhat removed from day-to-day ML development. Nonetheless, make sure you can talk about practical ML concerns, like how to deal with missing data or a buggy model. Deep learning is also a valuable subject area to know about.

Sample questions include:

• Does the vanishing gradient problem appear closer to the beginning or end of a neural network?
• Which activation function is better at mitigating the vanishing gradient problem, ReLU or sigmoid?
• What is regularization? What are the different types of it?
• If you have a million data points, would you use DNN or KNN? What's the difference in inference time?
• Explain data drifting.

Coding

Based on candidate reports, the final coding round usually features standard algorithmic coding questions of medium difficulty, in contrast to the more ML-focused ones that are emphasized on the first tech screen. You will be expected to generate working code on the fly (not pseudocode!), so be prepared to compile your program, run it, pass test cases, and so on. Banging out a solution that works and fulfills the requirements is more important than carefully optimizing every aspect of the implementation.

Sample tasks you might be given include:

• Write an LRU caching program.
• Write a program that takes prerequisites into account for scheduling courses.

ML system design

In this round, you’ll have to describe a technical solution for an open-ended problem. For senior roles in particular, this section will be weighted heavily in a potential hiring decision. Usually the problem you’re given will relate to one of Reddit’s product demands, such as ranking recommendations or detecting fraudulent content. A good system design answer starts by thinking through the task, considering what tools are needed, and foreseeing the pros and cons of your specific approach. As you lay out your design, you should briefly address the trade-offs you’re making as you go, but stay focused on presenting the overall picture.

Sample questions include:

• How would you design Instagram Reels?
• Design a Reddit clone.
• What tooling would you use to prototype a new feature? How will you scale it up?

Hiring manager round

The last round is a sit-down with the hiring manager for the team you’re applying to. Over the course of this section, you’ll answer questions about your past experiences, skills, and where you fit into the team. This is also a good opportunity for you to learn more about the role, and communicate your wants and needs as an engineer.

Approach this round as you would any other behavioral interview. Putting together a story bank of relevant past experiences is a great way to prepare.

Sample questions for this section include:

• Walk me through your most recent project.
• Name a time you overcame an adverse situation and turned it into a positive.
• Talk about a time when you disagreed with your team members over the direction of a project. How did you resolve it?

Additional resources

• Reddit’s tech blog at /r/RedditEng provides many valuable examples of projects you might work on, which can help you prepare for the system design and hiring manager rounds.
• Reddit’s company values and employee principles are laid out on their Values and Careers pages. Interviewers don't rigorously assess for these traits, but it can't hurt to know them.
• Book a mock interview with an experienced engineer with relevant skills so you’ll know what to expect.

FAQs

How should I prepare for a Reddit ML Engineer interview?

Practice coding problems. Look up Reddit’s tech blog at /r/RedditEng for insights into their product. Brush up on your ML interviewing skills using Exponent’s guides to ML coding and system design.

How much do Reddit ML Engineers make?

The average total compensation across software engineering levels at Reddit are:

• IC1 (entry-level): $145k
• IC2: $205k
• IC3: $270k
• IC4 (Senior): $391k
• IC5 (Staff): $431k
• IC6 (Principal): $890k

How long is the Reddit ML Engineer interview process?

Candidates report that they completed the entire interview sequence in 2-6 weeks, with three weeks being about the average.