As the world accelerates towards digitization and automation, artificial intelligence has emerged as one of the most rapidly growing fields that are powering the next chapter in technological innovation. The biggest technology companies in the world, Amazon included, are aggressively hiring engineers with AI and AI skills to help develop cutting-edge products that will define our future.
AI engineers are also known to draw lucrative salaries, mostly because of the unique set of skills they bring to the table. That said, if you are looking for a promising career in AI, applying for AI engineering roles at Amazon can be extremely exciting, given the scope of AI and the scale at which the company operates.
In this article, we’ll look at Amazon AI engineer interview prep tips, the interview process, and some sample questions to give you an idea of what to expect at the interview.
Here’s what we’ll cover in this article:
- Amazon AI Engineer Interview Process
- Typical Responsibilities of AI Engineers at Amazon
- Qualifications for Amazon AI Engineers
- Amazon AI Engineer Interview Questions
- Tips to Crack the Amazon AI Interview
Amazon AI Engineer Interview Process
The AI interview process at Amazon is very similar to the interview process for software engineers. The Amazon AI engineer interview process is essentially built to test your ability to solve complex problems and build algorithms to automate deep learning models.
The process typically consists of three main stages:
The Initial Phone Screen
A recruiter will contact you to confirm your interest in the position. You’ll be asked questions about your skills, compensation ( both current and expected), and why you want to work at Amazon. To get an interview call, make sure your LinkedIn profile is updated with the right keyword distribution to be detected by bullion search algorithms.
The Technical Phone Screen
You’ll be interviewed by a hiring manager responsible for driving the hiring process. This round will involve solving a coding problem and answering a few questions on theoretical AI and other AI concepts. The technical phone screen is a time-bound round and happens remotely via an interviewing tool or a shared document.
The Onsite Interview
This typically consists of 4 rounds — a coding round, an AI round, a behavioral round, and the bar-raiser round. The onsite essentially evaluates your problem-solving skills, your knowledge of AI algorithms and automating deep learning and predictive data models, and certain traits of your behavior, mostly those that you exhibit at the workplace. The bar-raiser round evaluates you against Amazon’s leadership principles to understand if you have the right motivation and attitude for the role.
For more information, check out Amazon AI Engineer Interview Process.
Typical Role of AI Engineers at Amazon
An AI engineer at Amazon has many responsibilities, including the following:
- Develop deep learning and AI algorithms for predictive models
- Collaborate with the software engineering and data engineering teams to develop predictive data models
- Design and develop scalable AI and AI systems
- Integrate AI and AI into business applications to automate a whole range of processes
- Designing and developing the architecture for data models and taking data-driven decisions by interpreting model metrics
Qualifications to Apply for AI Engineer Jobs at Amazon
The below qualifications are what Amazon looks for in the engineers applying for AI roles:
- While a bachelor’s degree in CS is good enough to apply to AI jobs at Amazon, a master’s degree in computer science, IT, or a related field is preferred.
- Familiarity and proven working knowledge of AI concepts, including data governance, application development, and infrastructure development.
- Proven working knowledge of building and designing algorithms for data models.
- Proven working knowledge of an object-oriented programming language, preferably Java, Python, or C++.
- 5+ years of experience in the field of AI.
Amazon AI Engineer Interview Questions
The interview questions asked at Amazon’s AI interview can be classified into three main categories.
These questions revolve around core data structures and algorithms. Below are some sample coding interview questions:
- Given an integer array arr of size n, find all magic triplets in it. A Magic triplet is a group of three numbers whose sum is zero. (Solution)
- Given a stream of integers, find the median of the set of integers read from the stream so far. If the median is a non-integer, round it down to the nearest integer. (Solution)
- Given an array of time intervals (in any order) inputArray, of size n, merge all overlapping intervals into one and return the resulting array outputArray, such that no two intervals in output Array are overlapping. (Solution)
- Given two arrays: 1) arr1 of size n, which contains n positive integers sorted in the ascending order. 2) arr2 of size (2*n) (twice the size of first), which contains n positive integers sorted in the ascending order in its first half. The second half of this array arr2 is empty. (Empty elements are marked by 0). Write a function that takes these two arrays, and merges the first one into the second one, resulting in an increasingly sorted array of (2*n) positive integers. (Solution)
- Inorder traversal - Process all nodes of a binary tree by recursively processing the left subtree, then processing the root, and finally the right subtree. Preorder traversal - Process all nodes of a binary tree by recursively processing the root, then processing the left subtree, and finally the right subtree. Given the inorder and preorder traversal of a valid binary tree, you have to construct the binary tree. (Solution)
Want access to more coding problems along with complete solutions? Visit the Problems page.
AI Interview Questions
Following are examples of the type of AI-related questions that you can expect during the interview:
- Explain CCA and ICA. How do you get a CCA objective function from PCA?
- Explain the process of finding thresholds for a classifier.
- Explain your idea to build a booking model to predict prices for accommodations on Airbnb.
- Which model among Random Forest Regression and Linear Regression would you prefer, and why?
- Explain the difference between Logistics Regression and Support Vector Machines.
Behavioral Interview Questions
Behavioral questions are an important part of the decision-making process at Amazon. These sample questions will give you an idea of the type of questions to expect at Amazon’s AI interview.
- How do you make sure to avoid burnout when you’re working on a challenging project?
- Have you had to adapt quickly when you started on a new project? Give us an instance.
- Tell us about a time when you disagreed with your superior?
- Tell us about a time when you missed a project deadline? How did you deal with the situation?
- Tell us about a time when you had to deal with a difficult client.
Tips to Crack the Amazon AI Interview
Below are some quick tips to crack the AI interview at Amazon:
- Begin your prep at least 10 weeks in advance, mostly because the extent of topics to cover are significantly vast.
- Practice whiteboard coding for the onsite interview, as recruiters can ask you to write code on a Whiteboard. If you don’t have prior practice, it can be extremely difficult to bring your thoughts together and write error-free code on a Whiteboard.
- Amazon lays enormous emphasis on behavioral interviews. The Bar-raiser round is designed specifically for that — to evaluate if you’re the right cultural fit at Amazon. So, do not ignore preparing for behavioral interviews.
- Structure your answers to questions about past projects in the STAR format. This way, you give recruiters a clear idea of what went down.
- Create a portfolio of your past projects and list details in the STAR format. Having a ready portfolio can put you miles ahead of the competition.
- While practicing problems, make sure you identify inherent solution patterns and apply them to new problems. This is the only proven way to amp up your problem-solving skills.
- Practice not just AI concepts but also core concepts in your choice of programming language.
Gear Up for Your Next AI Interview
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