Amazon Machine Learning Engineer Interview Process

Machine learning engineers play a crucial role in building algorithms to automate applications and deep learning data models. Considering Amazon’s enormous customer base and the wide spectrum of services it offers, the role of ML engineers is key to automating data-driven decision-making. 

If you are an ML engineer and want to apply for ML roles at Amazon, polishing your problem-solving skills and having considerable insight on data processing technologies along with the ability to build scalable ML systems is key. That said, knowing exactly what to expect at the interview is equally important. 

If you are preparing for a tech interview, check out our technical interview checklist, interview questions page, and salary negotiation ebook to get interview-ready! Also, read How Hard Is It to Get a Job at Amazon? and How to Get Software Engineering Jobs at Amazon for specific insights and guidance on Amazon tech interviews.  

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In this article, we’ll understand the Amazon Machine Learning interview process and dive deep into what to expect at the interview. 

Here’s what we’ll cover in this article:

• What Does Amazon Look for in ML Engineers?
• Amazon Machine Learning Engineer Professional Skills and Requirements
• Amazon Machine Learning Engineer Interview Process and Timeline
• Amazon Machine Learning Engineer Interview Questions and Tips
• Gear-up for your Next ML Interview

What Does Amazon Look for in ML Engineers?

Here’s what Amazon typically looks for in machine learning engineers:

• The ability to design and build scalable ML systems
• The Ability to automate predictive and Deep learning data models
• The ability to work cross-functionally with multiple teams, including data and software teams
• Excellent problem solving and analytical skills
• The ability to code-up algorithms to automate data-driven decision making

Amazon Machine Learning Engineer Professional Skills and Requirements

Let’s look at the skills and qualifications required to apply for machine learning positions at Amazon:

• A bachelor’s degree in computer science, mathematics, statistics, data analytics, IT, or a related field. A master’s degree may be required if you’re applying for senior ML positions.
• Professional experience of 5+ years in the field of machine learning.
• Experience in working LINUX/UNIX operating systems.
• Experience in working with big data technologies to leverage and process huge chunks of data
• Proven experience in working with Amazon Web Services technologies such as EC2, S3, Redshift, and EMR

Amazon Machine Learning Engineer Interview Process and Timeline

The interview process for machine learning engineers at Amazon essentially seeks to evaluate your problem-solving capabilities as well as your understanding and application of core ML concepts. 

There’s also a behavioral and bar-raiser round that aims to identify if you’d be the right cultural fit at Amazon. As for the timeline, the process is spread over 4-5 weeks, during which you’ll go through all your interview rounds. These are different stages in the interview process:

The Initial Recruiter Screen

This is pretty much the standard first round of interviews, where you’ll be contacted by a recruiter after you’ve applied for the position. Make sure your LinkedIn profile and resume are updated to give recruiters a clear idea of your skills and experience. 

During this round, the recruiter will ask you basic questions about your experience, why you’re looking to switch jobs, and your compensation expectations. If your skills are aligned with the requirements of the role, you’ll be invited to the technical phone screen interview. 

Related read: Amazon Phone Interview Questions

The Technical Phone Screen 

The technical phone screen round aims to evaluate your analytical and problem-solving capabilities. A hiring manager who conducts this round will ask you to solve a coding problem on core data structures and algorithms to see if your approach to problem-solving meets the standard. You’ll first be asked to brute-force the problem solution before writing code via a shared doc or an interviewing tool. 

The hiring manager will also ask you a couple of questions about core machine learning concepts. The questions will mostly be theoretical to understand the depth of your ML knowledge. If your performance is satisfactory, you'll be invited to the Amazon onsite interview. 

Related read: Amazon Coding Interview Questions

The Amazon Onsite Interview

The Amazon onsite interview is the real test of your professional attributes. The Amazon onsite, also known as “The Loop,” comprises the following rounds:

• The Coding Round: This round, usually conducted by a technical lead from the ML team, tests your programming abilities. The technical lead will ask you to solve a problem involving algorithms and test your general ability to apply concepts and arrive at the optimal solution. The coding round typically lasts 30 minutes.
• The Machine Learning Round: In this round, you’ll be asked questions around core ML concepts and a problem or two that involve applying those ML concepts. Questions can be around deep learning models, the Amazon ML engine, machine learning frameworks, and model optimization.
• The Behavioral Round: This round mainly seeks to understand your behavior in work-related situations. Questions in this round are mostly around workplace conduct, relationships with peers and superiors, client interaction, work-life balance, and productivity. 
• The Bar-Raiser Round: The bar-raiser round is unique to  Amazon interviews and essentially seeks to evaluate if you’re the right cultural fit. Questions in this round are based on Amazon’s leadership principles. Bar-raisers are specially trained to maintain the hiring bar at Amazon. Their job is to ensure that only top talent is filtered in. 

For more info, check out Amazon Behavioral Interview Questions and Amazon Leadership Principles Interview Questions

Amazon Machine Learning Engineer Interview Questions and Prep Tips

Cracking ML interviews at top tech companies requires a sound prep strategy that is comprehensive, exhaustive, and intensive. 

For interview questions and specific tips to nail the Amazon ML interview, check out our comprehensive piece on Amazon Machine Learning Engineer Interview Prep.

If your Amazon ML interview is around the corner and you’re looking for the best way to go about your prep, check out Interview Kickstart’s Machine Learning Interview Course to get comprehensive insights and direction on how to crack ML interviews. 

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