Disney Streaming Services Machine Learning Engineer Interview Questions + Guide in 2025

Disney Streaming Services is dedicated to creating engaging and innovative streaming experiences for audiences around the globe, leveraging cutting-edge technology and data-driven insights.

As a Machine Learning Engineer at Disney Streaming Services, your primary responsibility will be to design, develop, and implement machine learning models that optimize content recommendations and enhance the user experience on the platform. You will collaborate closely with data scientists, software engineers, and product managers to understand business requirements and translate them into scalable machine learning solutions. A strong foundation in algorithms, data structures, and programming languages such as Python or Java is crucial for this role. Additionally, proficiency in SQL for data manipulation and querying will be important, as you will be working with large datasets to inform your models.

An ideal candidate will possess a solid understanding of machine learning frameworks and libraries, as well as experience with cloud technologies to deploy models in production. Strong analytical skills, creative problem-solving abilities, and a passion for the entertainment industry are essential traits that will help you thrive in this dynamic environment. Your ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders will also be key to your success.

This guide will provide you with targeted insights and preparation strategies that will enhance your confidence and performance during the interview process at Disney Streaming Services.

The interview process for a Machine Learning Engineer at Disney Streaming Services is structured and thorough, designed to assess both technical skills and cultural fit within the company. The process typically unfolds as follows:

1. Initial Recruiter Call

The first step is a brief phone call with a recruiter, lasting around 30 minutes. This conversation primarily focuses on your resume and background, allowing the recruiter to gauge your professional experiences and motivations for applying to Disney. Expect questions about your previous roles, key projects, and why you are interested in working for Disney Streaming Services.

2. Technical Phone Screen

Following the initial call, candidates usually participate in a technical phone screen, which may last about 45 minutes. This interview is often conducted by a hiring manager or a senior engineer. During this session, you can expect to answer technical questions related to machine learning concepts, algorithms, and possibly some coding challenges. Be prepared to discuss your past work experiences in detail, as well as specific technical skills relevant to the role, such as SQL and data manipulation.

3. Onsite Interviews

The onsite interview process typically consists of multiple rounds (usually 3-5) of interviews with various team members. These interviews will cover a mix of technical and behavioral questions. Technical interviews may include problem-solving exercises, coding challenges, and discussions about machine learning frameworks and methodologies. Behavioral interviews will focus on your teamwork, communication skills, and how you align with Disney's values and culture. Each interview is designed to assess your fit for the role and the team.

4. Final Interview

In some cases, there may be a final interview with senior leadership or a cross-functional team. This round is often more strategic, focusing on how you can contribute to the broader goals of Disney Streaming Services. Expect to discuss your vision for machine learning applications within the company and how you can drive innovation.

As you prepare for your interviews, it's essential to familiarize yourself with the types of questions that may arise during the process.

Typically, interviews at Disney vary by role and team, but commonly, Machine Learning Engineer interviews follow a fairly standardized process across these question topics.

1. How do we select the best 10,000 customers for a pre-launch of a new show?

Amazon Prime Video wants to test the launch of a new show on 10,000 customers. How would you select the best 10,000 customers for this pre-launch?

2. Write a query to select the top five most expensive projects by budget-to-employee count ratio, accounting for duplicate rows.

Given two tables, projects and employee_projects, write a query to select the five most expensive projects by budget to employee count ratio. Ensure the query accounts for duplicate rows in the employee_projects table.

3. Write a query to show the number of users, transactions, and total order amount per month for 2020.

Write a query to show the number of users, transactions placed, and total order amount per month in 2020. Assume we are only interested in monthly reports for January to December.

4. Create a function rotate_matrix to rotate a 2D array by 90 degrees clockwise.

Given an array filled with random values, write a function rotate_matrix to rotate the array by 90 degrees in the clockwise direction.

5. Write a function to generate a transposed matrix and estimate linear regression parameters.

Given a matrix of X and y values, write a function to generate a transposed matrix and estimate the parameters for linear regression. Return the solutions as a list of [[A_T], [coefficients]].

6. Will increasing the number of trees in a random forest model always improve accuracy?

If you sequentially increase the number of trees in a random forest model, will the model’s accuracy continue to improve indefinitely?

7. What is the probability that a coin is double-headed and the next toss is a head after seeing 10 heads?

A jar holds 1000 coins, 999 fair, and one double-sided with two heads. You randomly pick a coin and toss it ten times, observing 10 heads. Calculate the probability that the coin is double-headed and the probability that the next toss will also be head.

Here are some quick tips on how you can ace your Disney Streaming Services machine learning engineer interview:

1. Develop Deep Communication Skills: Communication is key at Disney, both in technical and behavioral contexts. The interview process significantly emphasizes how well you can explain your thoughts, handle disruptions, and maintain clarity.

2. Focus on Core Technical Skills: Brush up on your primary machine learning concepts, programming skills in Python, and a solid understanding of ML pipelines. Practice similar questions on Interview Query to familiarize yourself with the kind of problems that may appear.

3. Cultural Fit Matters: Disney highly values their core values and mission. Prepare to answer questions about your favorite Disney characters and ensure that your answers reflect your alignment with their company culture and values.

What is the average salary for a Machine Learning Engineer at Disney Streaming Services?

What are the basic qualifications for a Machine Learning Engineer position at Disney Streaming Services?

To qualify for this role, you should have a Bachelor’s degree in Computer Science or a related field, at least 5 years of software engineer experience with 3+ years of relevant ML experience, familiarity with ML development lifecycle and frameworks (e.g., Triton, PyTorch), and be proficient in ML pipelines, algorithms, and statistical methods.

What skills are essential for succeeding in a Machine Learning Engineer role at Disney Streaming Services?

Successful applicants should have strong machine learning and software development skills, experience deploying and maintaining production ML models, and familiarity with Python ecosystem technologies such as Databricks, S3, and Spark. Excellent communication skills and the ability to work collaboratively in an agile environment are also crucial.

What should I expect in terms of company culture at Disney Streaming Services?

Disney fosters a business culture that values innovation, collaboration, and experimentation. The ML Engineering team at Disney encourages continuous learning and development and quality and user-centric development approaches.

The Machine Learning Engineer role at Disney Streaming Services offers an exciting opportunity to make a significant impact on Disney’s digital ecosystem. By applying your machine learning expertise and software development skills, you’ll contribute to shaping cutting-edge streaming solutions while collaborating with cross-functional teams.

If you want more insights about the company, check out our main Disney Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Disney’s interview process for different positions.

You can also check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!