TikTok Machine Learning Engineer (MLE) Interview Guide

Learn how to prepare for the TikTok machine learning engineer interview with this in-depth guide.

Machine learning engineers (MLEs) are the driving force behind innovation at TikTok, researching and optimizing the platform's cutting-edge algorithms. Whether enhancing the user's feed experience or refining TikTok’s ad targeting capabilities, they shape how billions of users interact with ByteDance’s beloved social media app.

If you’re interested in contributing to TikTok’s mission to “inspire creativity and bring joy” from a technical, data-driven perspective, machine learning could be an excellent fit. Below, we cover what MLE work looks like and how to prepare for the TikTok machine learning engineer interview process.

What Does a TikTok MLE Do?

Machine learning is central to TikTok’s short-form video app. The platform’s recommendation system relies on a complex architecture of ML techniques, including collaborative filtering, deep learning, and natural language processing (NLP). Engineers research, design, and implement these ML systems to optimize the platform’s infrastructure and deliver a captivating user experience.

TikTok’s ML engineers work across many teams, including:

• Applied Machine Learning
• App Ads and Gaming
• Business Integrity
• E-commerce Global Supply Chain and Logistics
• Risk Data Mining
• Search Ads
• Shop Ads
• Trust & Safety

These teams are further divided into smaller internal divisions. For example, the Applied Machine Learning (AML) team includes subteams focused on Data, Recommendation Systems, and Innovation.

ML engineers are in high demand throughout TikTok’s product ecosystem. Besides collaborating with fellow engineers, they work closely with product managers and data scientists to develop and optimize recommendation systems, ad ranking, and search algorithms.

In terms of compensation, the average MLE salary at TikTok ranges from $211,000 to $319,000 per year, including bonus and stock.

What Are the Typical Job Requirements for a TikTok MLE?

TikTok hires ML engineers with a variety of focuses, including:

• Recommendation Algorithms
• Ecommerce
• Ads
• Risk Data Mining
• Supply Chain

Each focus area brings unique job responsibilities as an MLE. However, generally speaking, there are a handful of baseline criteria sought after in all TikTok ML engineer candidates:

• Bachelor’s or advanced degree in Computer Science or a related technical discipline
• A minimum of 3 years of relevant industry experience for junior roles, and 5-7 years for senior roles
• Technical proficiency with C/C++/Python and programming skills
• Effective communication and teamwork skills

Although ML engineering is a highly technical job, the value of interpersonal communication skills cannot be understated. Emphasizing your ability to work cross-functionally and with people from diverse backgrounds can benefit applications for virtually any role at TikTok.

Since every role has unique requirements, we’ve included examples for a few different machine learning positions. Below are the requirements listed in a posting for an MLE on TikTok’s Search Ads team.

Required Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, or other relevant majors
• Excellent programming, debugging, and optimization skills in general-purpose programming languages
• Ability to think critically and formulate solutions to problems clearly and concisely

Preferred Qualifications:

• Experience with one or more general-purpose programming languages, including but not limited to: Go, C/C++, Python
• Good understanding of one of the following domains: ad fraud detection, risk control, quality control, adversarial engineering, and online advertising systems
• Good knowledge in one of the following areas: machine learning, deep learning, backend, large-scale systems, data science, full-stack

Compare those with the requirements for an MLE on TikTok’s Applied Machine Learning (AML) team, focused on ML Infrastructure.

Required Qualifications:

• Bachelor’s or higher degree in Computer Science or related fields from accredited and reputable institutions
• Proficient in C/C++/Python, with solid programming skills
• Familiar with deep learning frameworks (TensorFlow/Pytorch)
• Experience in developing and deploying large-scale systems
• Ability to work independently and complete projects from beginning to end in a timely manner
• Good communication and teamwork skills to clearly convey technical concepts to other teammates
• Experience improving core machine learning infrastructure (TensorFlow, Pytorch, and Jax)
• 3+ years of industry experience with a solid theoretical foundation in machine learning

Preferred Qualifications:

• Experience contributing to an open-sourced machine learning framework (TensorFlow/PyTorch)
• Experience with big data frameworks (e.g., Spark/Hadoop/Flink) and resource management and task scheduling for large-scale distributed systems
• Strong background in one of the following fields: Hardware-Software Co-Design, High-Performance Computing, ML Hardware Acceleration (e.g., GPU/TPU/RDMA), or ML for Systems

Recommendations Before You Apply for TikTok MLE Roles

• Get familiar with TikTok’s features. You probably know TikTok as the popular short-form video platform that engages millions of users, but there’s a lot more to it—like its TikTok for Good and TikTok for Developers programs. Learning about TikTok’s mission and where it currently stands among lawmakers is an excellent way to show your interest as a candidate. Familiarize yourself with its unique programs and offerings so that you can confidently discuss them and demonstrate your enthusiasm for the company in your interviews.
• Understand TikTok’s company culture. Many TikTok employees describe the company’s culture as rigorous and demanding. Keep this in mind as you apply and begin the interview process. Think about your long-term career goals and how an MLE role at TikTok fits into the bigger picture of your professional journey. Also, consider strategies to maintain a healthy work-life balance and avoid burnout.
• Emphasize your ability to work cross-culturally. As a subsidiary of ByteDance, a global technology company headquartered in Beijing, working at TikTok often means collaborating with a diverse range of team members. Beyond New York and Los Angeles, TikTok has offices in London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul, and Tokyo. Because of this, TikTok values open-minded candidates who work well with people of different backgrounds. If you have experience working with international teams, be sure to highlight it in your application.

Interview Process

TikTok’s machine learning interview process varies among candidates. According to the TikTok engineer we spoke with, there is no standardized interview process. Across the company’s various teams, recruiters have unique hiring processes.

However, applicants generally describe going through 3-4 interview stages:

• An online coding assessment for recent grads
• A recruiter phone screen or a brief email questionnaire designed to find out HR basics, such as your earliest start date, as well as why you’re interested in working for TikTok
• A technical phone screen made up of coding, data structures, and algorithms questions
• An interview loop that consists of 3-5 hour-long technical rounds

The interview loop is virtual and takes place over multiple days. After passing an interview, you’ll be invited to a subsequent round that may take place 1-3 weeks later.

Past candidates report a variety of formats in the final interview loop. As such, you can expect a single interview round to be structured in any one of the following ways:

• A 45-minute deep dive into your resume followed by 15 minutes of medium-level coding questions
• 30 minutes of machine learning fundamentals based on your resume, then 30 minutes for coding, data structures, and algorithms problems
• 20 minutes of machine learning questions and 30 minutes of medium- or hard-level data structures and algorithms questions

Below, we provide pointers on what to expect in each stage and how to prepare.

Online Assessment and Recruiter Screen

Similar to the TikTok software engineer interview process, recent grads applying for one of TikTok’s machine learning roles typically start off with a 60-minute online coding test hosted on HackerRank. Experienced candidates, on the other hand, generally talk with a recruiter via email before moving directly to the technical round.

Candidates who have taken the assessment report that it typically includes five total questions, a combination of multiple-choice and wide-ranging technical problems.

However, the exact format may vary. The TikTok MLE we spoke with faced four coding problems, including one easy, one medium, and two hard.

After taking the test, candidates are scored, and their results create something of a shortlist for recruiters. Top-performing candidates get priority. However, even if you didn’t perform the best on the assessment, you may still be contacted by a recruiter.

The recruiter phone screen is more common for recent grads than for experienced candidates. It typically involves a brief call to ask straightforward behavioral questions and find out HR basics, such as your earliest start date and visa status. However, some candidates report that instead of a phone call, recruiters may send a questionnaire with the same questions via email.

Regardless, it’s best to practice answering some basic introductory questions. Examples include:

• Tell me about yourself.
• Why TikTok?
• What did you do in your last role?
• Take me through your resume.

Machine Learning Fundamentals

Machine learning at TikTok focuses on using complex systems and algorithms to enhance user experience, optimize content delivery, and ensure platform security. Candidates should have a strong foundation in machine learning theory and practical experience with implementing machine learning algorithms.

Prepare to answer questions about your background in machine learning and AI, and share details about your past projects. TikTok’s interviewers are looking for candidates with a solid understanding of conceptual machine learning. Expect scenario-based questions with problem-solving and ideation at their core.

For instance, one anonymous candidate reported being asked, “We want to execute [X] in a specific order. Design a function to execute this.” Remember to consider possible edge cases and communicate these to your interviewer.

It’s worth reviewing recommendation system algorithms since these are key to TikTok’s platform. Below are a few resources to get started:

• “How TikTok Recommends Videos #ForYou,” a blog post from TikTok
• “Monolith: Real Time Recommendation System With Collisionless Embedding Table,” a paper by TikTok’s own research team

Below are sample machine learning questions candidates have reported being asked:

Coding

TikTok’s coding interviews are known for being incredibly challenging. According to one TikTok interviewer, there is no internal interview bank of questions. Instead, interviewers are free to choose their own questions to challenge candidates.

Given this variability, many candidates recommend preparing for TikTok’s coding rounds by practicing programming problems, also known as Data Structures & Algorithms questions.

• Start with easy problems. Begin by solving a few easy coding problems, such as Move Zeros to End, to get into the rhythm of problem-solving before transitioning to medium and hard problems.
• Focus on understanding solutions. Take time to understand the logic behind each solution by reviewing common programming patterns and strategies, like graph search.
• Practice with other people. You can learn a lot from seeing how others solve problems. On Exponent, you can watch mock interviews, read community answers, and even practice a mock coding interview.

The same MLE, who has experience interviewing candidates for TikTok’s technical screen, also shares his three criteria for assessing candidates:

1. Communication: How does the candidate interact with the interviewer? Do they offer any explanations as they work on a problem, e.g., why they chose a certain variable or algorithm?
2. Problem-solving skills: Does the candidate solve the given problem?
3. Coding quality: What does the candidate’s code look like? Is it clear and efficient?

TikTok Career’s page similarly emphasizes the importance of communication during this interview:

"We have noticed that strong candidates tend to ask relevant questions before writing the code, diagram the problem, validate their assumptions, and check their work constantly without being prompted. While solving a problem, pay keen attention to the efficiency of your solution to make sure it's not unnecessarily complicated."

Below are coding questions past candidates have reported being asked:

• Given a graph, detect whether it is bipartite.

• Given a 2D image containing 0s and 1s, find if the image contains a loop created by 1s which contains 0s.

• Find the median of two sorted arrays.

• Sort a list by alphabetical ascending order.

  Note

  Check out Exponent’s extensive ML Coding Questions course as a resource for improving your ability to solve ML-specific coding questions while also clearly articulating your process.

Behavioral

TikTok’s machine learning interview does not have a dedicated behavioral round. However, as you move through the interview loop, interviewers may spend a few minutes asking behavioral questions before shifting gears into technical ones.

Many candidates also report going through their resume and answering questions about past ML projects during their interview. To prepare, come up with a brief but detailed summary of your past projects, including their main outcomes and takeaways. Practice talking about them with friends.

It’s also worth brainstorming a handful of personal stories that might be relevant to your prospective role. Think of past professional experiences that align with ByteDance and TikTok’s company values, which include:

• Always Day 1. Maintain an entrepreneurial mindset. Keep pioneering and innovating instead of relying on resources or past achievements.
• Champion diversity and inclusion. Value individual differences, and focus on people’s unique strengths.
• Be candid and clear. Speak your mind. Drive communication and form conclusions with facts, not assumptions or emotions.
• Seek truth and be pragmatic. Be an independent thinker. Seek direct experience and firsthand data and information.
• Be courageous and aim for the highest. Dare to take calculated risks for bigger gains with a focus on return on investment.
• Grow together. Show patience and resilience in the face of short-term fluctuations. Solve problems together.

When answering questions, we recommend using the STAR format. This involves structuring your answers as follows: situation, task, action, and result.

Sample behavioral questions worth practicing include:

Tips and Strategies

• Coding practice is essential. Technical interviews are at the heart of the ML engineer interview process. The TikTok MLE we spoke with advised incorporating coding practice into your routine, sharing, “I made a target of solving five problems a day. Within three months, I was prepared for interviews.” Besides building confidence in his technical skills, he described the practice as helping sharpen his ability to break complex coding problems into different pieces.
• Share your thought process while coding. Articulating your thought process clearly is essential to your success during TikTok’s technical interviews. Think out loud so the interviewer can understand your problem-solving approach. Successful candidates typically ask pertinent questions upfront, outline the problem, validate assumptions, and review their work. Mock interviews are a great way to strengthen these critical communication skills.
• Stay flexible. Your interview might be scheduled for a non-traditional time depending on who your interviewer is and where they’re based. (Remember, TikTok’s workforce is spread across the globe.) Maintain an enthusiastic attitude throughout the process and demonstrate a willingness to be flexible as a candidate. This can be a great way to set yourself apart as a positive and hard-working prospective hire.
• Don’t hesitate to ask for clarification before answering questions. Some TikTok applicants report struggling in their interviews due to communication issues with their interviewers. Given TikTok’s international team, your interviewer’s first language may not be English. If faced with language challenges, ensure you fully understand the question before responding, and be polite and patient.

Additional Resources

• TikTok Career’s Interview Tips
• TikTok Career’s FAQs
• [Machine Learning Engineer Interviews Course](https://www.try

exponent.com/courses/ml-engineer)

• Top TikTok Machine Learning Engineer Interview Questions
• Top TikTok Interview Questions
• Top Machine Learning Engineer Interview Questions
• TikTok Software Engineer Interview Guide
• TikTok Data Scientist Interview Guide

FAQs

• Does TikTok offer MLE internships and junior positions? Yes! TikTok offers a variety of ML and software engineering internships, as well as junior ML engineer positions for recent graduates or individuals with less related industry experience. Interns who perform well may even receive a return offer. Visit TikTok’s early careers page for more information.
• Where does TikTok have offices? As an international product and subsidiary of ByteDance, TikTok has many offices throughout the world. TikTok’s global headquarters are in Los Angeles and Singapore, with additional office locations including New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.