It takes years of experience in software engineering and data science to become a machine learning (ML) engineer at Apple. With the rise in demand and popularity of ML engineer jobs and Apple’s reputation as a top-notch employer, machine learning jobs at Apple are difficult to crack but worth the effort, both in equal measure.
If you are preparing for a machine learning engineer role, check out our technical interview checklist, interview questions page, and salary negotiation e-book to get interview-ready! Also, read Google Machine Learning Engineer Interview Process and Amazon Machine Learning Engineer Interview Process for specific insights and guidance on machine learning interviews at FAANG.
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We have put together the ultimate guide on everything you need to know about preparing for the Apple machine learning interview. Here’s what we will cover in this article:
Machine learning enables a computer to learn on its own or with little initial help. It uses four broad types of algorithms — supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning.
Artificial intelligence uses three main techniques — searching techniques, knowledge representation, and reasoning.
A machine learning engineer uses machine learning techniques to solve real-life problems and build software. An artificial intelligence engineer uses artificial intelligence algorithms to solve the same problems.
As an Apple machine learning engineer, you will be responsible for extracting value from available data at Apple, along with data collection, cleaning, preprocessing, training and deploying models, and production. Some of your responsibilities as an Apple machine learning engineer will be to:
To become a machine learning engineer at Apple, you should have a bachelor's degree in computer science or equivalent with at least 5+ years of hands-on experience working with machine learning models.
Besides the educational qualifications and experience, here are some key qualifications you should consider working on before applying for the role:
Like most other FAANG companies, the Apple interview structure for a machine learning engineer role comprises a phone screen followed by on-site interviews. The interviewers are particularly interested in talking about your past projects with a special emphasis on deep learning and the implementation of machine learning concepts.
Other questions will be based on coding skills, which will also test your optimization skills, time management, and space complexity management.
Typically, the Apple machine engineer interview process consists of the following rounds:
Here’s a coding cheat sheet to help you prepare for your Apple machine learning engineer interview.
Questions during a machine learning engineer interview cover a wide range of technical topics. We’ve put together some topics you should pay attention to during your ML tech interview prep:
Data science promises to be the future of technology. While preferred skills keep changing with time, here are some essential ones you will need to brush up on while preparing for your Apple machine learning interview:
Based on inputs from former candidates and hiring managers, we have created a study guide to help you prepare for your Apple machine learning interview:
SQL questions may need an aggregation with a filter, and others may need a few joins, recursions, and analytic functions. Following are a couple of sample SQL interview questions:
1. Analyze the given data on employees and departments of a company:
Columns: id, first_name, last_name, salary, department_id
Types: int, varchar, varchar, int, int
Columns: id, name
Types: int, varchar
From the above data, pick out the top 3 departments with a minimum of 10 employees and rank them as per the percentage of employees earning a salary of over $100,000.
2. You’re given a dataset of a company’s employees and departments:
id – int
first_name – varchar
last_name – varchar
salary – int
department_id – int
id – int
name – varchar
Using the information above, write an SQL query that selects the engineering department’s second-highest salary. Furthermore, your query should select the subsequent highest salary if more than one individual earns the highest salary.
To solve operational programming, you must know how to use arrays and dictionaries. Following are examples of problems you can expect:
Recommended reading: How to Crack a System Design Interview
For more problems on data structure and algorithms, with solutions, visit the Problems page.
In addition to the above-listed type of questions, you can also expect some questions related to machine learning during the interview:
Related reading: Apple Interview Questions
Here are some additional essential tips to help you prepare for your machine learning engineer interview at Apple:
Q. How much does an Apple machine learning engineer make on average?
The average annual Apple machine learning engineer salary in the United States is $131,000, along with numerous perks and benefits. For more information, read Apple Machine Learning Engineer Salary.
Q. I have just started my software engineering career. Can I still become a machine learning engineer?
Machine learning positions at most tech companies are reserved for candidates with good experience (usually 3+ years) in the field. However, there are ways to start preparing yourself for a machine learning role early in your career. Experts at Interview Kickstart can show you how. Register for a free webinar today!
Think it is too difficult to crack Apple’s machine learning interview process? Not if you sign up with Interview Kickstart!
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