Disney Streaming Services Machine Learning Engineer Interview Questions + Guide in 2024

Disney Streaming Services is a top-tier division of The Walt Disney Company, pivotal in delivering transformative digital experiences through innovative streaming solutions. As a Machine Learning Engineer, you’ll play an integral role in driving and enabling the usage of machine learning across various domains.

In this position, you will collaborate with data science teams to produce and maintain ML models, develop tools and services to simplify the ML development lifecycle, and ensure seamless integration within Disney’s production ecosystem. Solid machine learning expertise, strong software development skills, and a passion for user-centric solutions are essential.

This guide will walk you through the interview process, commonly asked Disney Streaming Services machine learning engineer interview questions, and essential tips to help you land this sought-after role. Let’s get started!

The interview process usually depends on the role and seniority; however, you can expect the following on a Disney Streaming Services machine learning engineer interview:

Recruiter Call Screening

If your application stands out, a Disney Talent Acquisition Team recruiter will contact you to verify key details like your experiences and skill level. Behavioral questions may also be asked during this stage.

Sometimes, the hiring manager may join the call to answer your queries about the role and the company. They may also engage in surface-level technical and behavioral discussions. The recruiter call typically lasts about 30 minutes.

Technical Virtual Interview

Passing the recruiter round will lead you to the technical screening round. This interview is conducted virtually and involves video conferencing and screen sharing. This stage may involve technical questions about ML systems, model evaluation, and Python programming.

For a Machine Learning Engineer role, you can expect take-home assignments focusing on ML model development, deployment, and evaluation. Your knowledge of algorithms, statistics, coding, and machine learning fundamentals will be tested.

Depending on the seniority of the position, you might also get case studies or scenario-based problems.

Onsite Interview Rounds

You will be invited to the onsite interview rounds if you clear the technical virtual interview interview. These rounds will further evaluate your technical skills, coding proficiency, and ML modeling capabilities. You might go through multiple interview sessions during your day at the Disney office, including live coding and system design discussions.

The final stage usually involves an interview loop with team members, covering technical deep dives and team-fit assessments.

Typical Interview Questions

1. Name a time you didn’t see eye to eye with a Developer.
2. How do you manage the React component state?
3. Who is your favorite Disney character, and why?
4. Explain when you told a story through data to a non-technical audience.
5. Can you talk about an analytics project you completed from end to end?
6. What software are you comfortable and proficient in using?
7. Why do you want to work here?

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!