The role of AI engineers has become significantly prominent in recent times, with top tech companies actively hiring for artificial intelligence and machine learning roles. With automation at the forefront of modern technological innovation, an increasing number of software engineers are educating themselves in ML and AI to upskill themselves and stay relevant to present-day market demands.
Amazon is no stranger to the discernible AI trend. In fact, the company has been one of the pioneers of AI technology, leveraging ML and Ai to improve consumer experience and engagement.
If you’re a software engineer, software developer, engineering manager, or tech lead preparing for tech interviews, check out our technical interview checklist, interview questions page, and salary negotiation ebook to get interview-ready! Also, read How hard it is 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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If you are an AI engineer looking to apply to jobs at Amazon, this article is for you. We’ll discuss the various stages of the Amazon AI engineer interview process and understand what it takes to crack AI interviews at Amazon.
Here’s what we’ll cover in this article:
- The Role of AI Engineers at Amazon
- Qualifications for AI Engineers at Amazon
- Amazon AI Engineer Interview Process
- Amazon AI Engineer Interview Tips
- Get Ready for your Next Amazon AI Interview
The Role of AI Engineers at Amazon
An AI engineer role at Amazon entails the following key responsibilities:
- Develop algorithms to automate data models and deep learning models
- Build novel artificial intelligence solutions to train and guide machine learning models
- Develop scalable machine learning systems
- Define the requirements for ML systems based on data metrics
- Design and build algorithms that automate predictive data models
- Coordinate with data science and data engineering teams to automate processes and internal applications
- Build algorithms that guide and define user interaction and consumer engagement
Qualifications for AI Engineer Roles at Amazon
These are some of the basic qualifications required to be an AI engineer at Amazon:
- A bachelor’s degree in statistics, mathematics, computer science, IT, or a related field that involves building and working with AI models
- Minimum 4 years of experience in the field of ML/AI
- Proven experience in working with AI frameworks and ML technologies
- Proven experience in data governance and infrastructure development
- Proven experience in planning and building the architecture for scalable AI and ML systems
- Proficiency in an object-oriented programming language
- Working knowledge of big data technologies
- Working knowledge of AI, ML, and data modeling tools
- Proven experience in building deep learning and predictive data models
The Amazon AI Engineer Interview Process
The Amazon AI interview process consists of three main stages. The process is usually similar for most tech interviews at Amazon.
The Initial Phone Screen
The initial phone screen will be with a recruiter from Amazon’s HR department. The recruiter will ask you questions pertaining to your level of experience, skills, your current and expected compensation, and why you’re specifically looking to apply at Amazon.
The initial phone screen is more of an informal conversation. If your experience level and skills satisfy the requirements of the position, you’ll be called for the technical phone screen Interview.
Recommended Reading: Amazon Phone Interview Questions
Technical Phone Screen Interview
The technical phone screen interview is the first main round in the Amazon Ai interview process. This round is essentially a test of your problem-solving and analytical skills. Your knowledge of AI and ML concepts is also evaluated in this round.
You’ll be asked to solve a problem on core data structures and algorithms via an interviewing tool or a shared document. The hiring manager conducting this round will first ask you to brute force the solution to understand your analytical approach, after which you’ll be asked to write code. The approach you take to arrive at the most optimal solution is what is keenly observed in this round.
The hiring manager will also ask you questions about your AI skills, theoretical AI concepts, and your overall experience in the field. If your performance in this round is satisfactory, you’ll be invited to the Amazon onsite interview.
Recommended Reading:How to Prepare for and Crack Phone Screen Interviews at FAANG
The Amazon Onsite Interview
The onsite interview is the last step in the Amazon AI interview process. The onsite tests various a bunch of technical and behavioral attributes before hiring managers decide to make you an offer.
The onsite typically consists of four main rounds:
- The Coding Round: The hiring manager in this round will ask you 1-2 coding problems in algorithms and core data structures. Just like in the technical phone screen, you’ll first have to Brute Force the solution before writing code, either on a document or a whiteboard. The hiring manager might tweak the initial problem statement to closely evaluate your approach to finding the most optimal solution to the problem.
- The AI/ML Round: In this round, you can expect a practice concept-oriented problem in AI/ML. You can also expect a few theoretical questions. You’ll also be asked to design an algorithm for a specific predictive or deep learning data model.
- The Behavioral Round: The behavioral round mostly tests your response to work-related situations. Questions asked will be around your relationship with superiors and colleagues, productivity and conduct in a workplace, past projects you worked on, and general workplace challenges.
- The Bar-Raiser Round: Bar-raisers are employees trained to protect the hiring bar at Amazon by recruiting strong and worthy talent. In this round, you can expect questions around Amazon’s leadership principles along with a few questions on your experience and projects. Bar-raisers typically evaluate if you’re the right cultural fit at Amazon. They test if you display the right attitude and motivation to fulfill the responsibilities of your role.
To know more about Amazon interviews and the importance of being properly prepared for them, read our article on How Hard it is to Get a Job at Amazon.
Tips to Crack the Amazon AI Engineer Interview
Below are some noteworthy tips to keep in mind while preparing for the Amazon AI engineer interview:
- Begin your prep at least 8 weeks before your interview.
- Practice a good number of problems — at least one or two every day on data structures and algorithms, for 8-10 weeks before your interview.
- Identify patterns in problems and classify problems based on identical solution patterns. Apply these patterns to solve new problems. This is the best way to build your problem-solving skills.
- Dedicatedly prepare for the behavioral interview.
- Practice at least 8-10 mock interviews with instructors from FAANG companies.
- Think aloud your solution and voice out your thoughts during the coding round of the interview.
Recommended Reading:How to Crack a Coding Interview With 2 Months of Prep
Get Ready for Your Next AI Engineer Interview
If you want to know the best way to nail your upcoming Amazon AI interview, register for our free webinar. We’ve trained 6,000+ students to land amazing offers at the biggest tech companies. With expert instructors who are FAANG hiring managers and tech leads themselves, we know exactly what it takes to crack tough technical interviews at the biggest companies.
Our alums have landed multiple offers with FAANG and tier-1 companies, with minimum average pay hikes of 49%.
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