Apple Interview Tips: Real Questions Answers & OA Interviews

Apple Interview Prep: Questions & OA Walkthrough

Apple OA Interviews - Apple Interview Assist

Apple, the world's top developer and marketer of smart wearable devices(math.) genusIts hiring process also carries the unique Apple stamp of approval. The whole journey starts with a very thorough resume screening, which is not just about how technically competent you are, but also whether you coincide with the kind of Apple culture where innovation is paramount and excellence is pursued. Every detail of your resume should strive to align closely with the job description you're applying for, with the relevance of past projects and your tech stack being the focus.

After you pass the resume screening, Apple may send you an online test (OA), which focuses on your programming skills and problem-solving abilities, and is a critical first step in determining whether or not you'll be able to move on. If you do well on the OA, you'll usually get an initial phone call.

Next, comes one or two rounds of technical phone interviews. These interviews will assess your technical skills and problem-solving abilities through programming exercises and in-depth discussions of each of your past projects and experiences. Phone interviews are not only a technical examination, but also an excellent opportunity for you to demonstrate your communication skills, which are critical in an environment like Apple's that emphasizes teamwork! Be prepared for questions about algorithms, data structures, and system design.

Pass the phone interview and congratulations! You are about to have the most exciting and challenging on-site interview session. Typically there are three to six rounds of interviews in a variety of formats, ranging from in-depth one-on-one conversations with prospective colleagues to discussions with senior team members. The interviews are a comprehensive blend of technical, system design, and behavioral content, designed to look at all aspects of your technical prowess and whether you truly fit into the Apple culture.

You will be asked to work on real-world problems that are often derived from scenarios that Apple engineers encounter on a daily basis. At the same time, be prepared to clearly articulate your thought process and demonstrate your ability to collaborate. Overall, Apple's onsite interviews are known for their high level of difficulty and depth, and are a critical test of whether you have what it takes to work in an environment like Apple's that strives for excellence and innovation.

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Job Type

Mobile Engineer

Job responsibilities: develop and maintain applications or frameworks for iOS, macOS, watchOS, tvOS and other platforms, focusing on user experience, performance optimization.

Interviews examine technical points: Swift/Objective-C language features, UIKit, AppKit, SwiftUI, multithreading/concurrency, memory management, Apple platform APIs, UI/UX principles.

front-end engineer

Responsibilities:Develop and optimize user-facing web application interfaces or user interfaces for product software to ensure compatibility, performance, and user experience.

Interviews examine technical points: JavaScript (and modern frameworks such as React, Vue, Angular, etc., or Apple's internal technology), HTML, CSS, Web performance optimization, browser work, responsive design, front-end architecture.

MLE

Responsibilities:Design, develop, train and deploy machine learning models and related toolchain for Siri, camera, health and other functions.

Interviews: Machine learning algorithms and theories, deep learning frameworks (TensorFlow/PyTorch, etc.), data processing and feature engineering, model evaluation and optimization, Python programming, large-scale ML system design.

DE

Responsibilities:Build, maintain and optimize data pipelines (ETL), data warehouses, data lakes, process large scale data to support analytics, ML, etc.

Interviews examine technical points: SQL, Big Data technologies (Spark/Hadoop/Hive, etc.), data modeling, data quality, data processing frameworks, distributed computing fundamentals.

The Key Areas of Tech Interview

When preparing for your Apple Software Engineer interview, it's important to focus on solidifying your skills in Basic Data Structures and Algorithms (Basic DSA), Dynamic Programming, and Two Pointers. According to LeetCode, these areas dominate programming questions. While honing these skills, you should not overlook the possibility of encountering more complex challenges such as Advanced Data Structures and Backtracking. Although these topics appear less frequently, they may still come up to test your deeper understanding of programming practices.

Features	Percentage
Misc	20.6%
Simulation	1.6%
Two Pointers	12.7%
Adv. Data Structure	4.8%
Backtracking	4.8%
Basic Data Structure and Algorithm	23.8%
Binary Search	1.6%
Heap	4.8%
Graph	1.6%
Dynamic Programing	11.1%
Depth-First Search	7.9%
Breadth-First Search	4.8%

Interviews for Software Engineers at Apple can be challenging, and are often considered equal to or more difficult than at other FAANG companies. Candidates are often presented with problems involving Dynamic Programming, which are often difficult to solve under strict time constraints. Despite the challenges, these interviews are centered on evaluating a candidate's problem solving skills, which can be assessed through the CSOAsupport The guide was upgraded.

If you look at the percentage of difficulty of the questions, only 31.71 TP6T were easy questions, the percentage of medium difficulty questions was as high as 56.41 TP6T, and the remaining 11.91 TP6T were high difficulty interview questions.

Questions and Difficulty

Common Interview Questions	Examining technical points	degree of difficulty or ease
The farthest building you can reach.	Pile, miscellaneous	medium difficulty
Integer to English words	backtracking algorithm	challenging
Bag of Tokens	Basic data structures and algorithms, miscellaneous, double pointers	medium difficulty
Minimizing bias in arrays	Advanced data structures, heaps, miscellaneous.	challenging
LRU cache	Basic Data Structures and Algorithms	medium difficulty
Longest Incremental Subsequence II	Advanced data structures, dynamic programming, miscellaneous.	challenging
Partition the array according to the given pivot	Analog, Dual Pointer	medium difficulty
valid word square (in grammar)	Basic Data Structures and Algorithms	liable (to)
Creating the Hello World Function	Advanced Data Structures, Dynamic Programming	liable (to)
sequential figure	backtracking algorithm	medium difficulty

Apple OA (online assessment)

The first step of Apple's technical interview online assessment (OA), in fact, is mainly to quickly and efficiently examine your programming fundamentals and problem-solving ability under a certain time pressure, to see if your basic skills are solid, is a way to initially screen the candidates, so ah, do not put too much pressure on yourself to prepare for this stage, focus on consolidation of the most core Data Structures and Algorithms (DSA), especially the following Arrays, strings, chained lists, trees, hash tables are the basic structures, as well as sorting, searching, double pointers, sliding windows, recursion, these basic algorithms, it is very important to understand their time and space complexity. Brush up on some of the moderate or easy difficulty questions on LeetCode, mainly to practice writing correct and moderately efficient code in a limited amount of time and to familiarize yourself with the online programming environment.

Mobile Engineer

The Software Engineer interview is the most comprehensive of Apple's technical interviews for the Computer Science Fundamentals position.

Examine the technical points:
- Data Structures and Algorithms (DSA): This is the core of all Software Engineer positions and covers data structures such as arrays, chained lists, stacks, queues, trees, graphs, hash tables, heaps, and other data structures, as well as common algorithms such as sorting, searching, dynamic programming, greedy algorithms, backtracking, and others. Candidates are required to be proficient in analyzing time complexity and space complexity.
- System Design: Examines the ability to design scalable, reliable, and efficient software systems, including distributed systems, database design, API design, and caching strategies.
- Programming skills: Proficiency in at least one major programming language (e.g. Swift, Objective-C, C++, Java, Python) and the ability to write clear, efficient and robust code.
- Operating systems, computer networks, database principles: Level of understanding of these fundamentals, especially in areas related to specific teams (e.g. iOS, macOS development).
Interview Questions :
1. In an array of integers, find the index of the two numbers whose sum is a specific target value. The requirement to find the index of the two numbers in the $o (n)$ solution within the time complexity of the
2. Implement a least recently used (LRU) cache.
3. Design a URL short T H service (e.g., Bitly).
4. Given the root node of a binary tree, flip the tree and return its root node.
5. Explain the difference between processes and threads and their role in the operating system.

front-end engineer

Interviews for front-end engineers focus on mastery of the web technology stack and front-end-specific problem-solving skills, in addition to general programming skills.

Examine the technical points:
- HTML, CSS, JavaScript basics: In-depth understanding of the features, DOM manipulation, event mechanism, prototype chaining, scopes, closures, etc. of these three languages.
- Front-end frameworks/libraries: In-depth knowledge and hands-on experience with at least one major front-end framework (e.g. React, Angular, Vue), understanding its design thinking and working principles. Sometimes also examine the ability to build complex interfaces without relying on frameworks.
- Performance Optimization: Understand front-end performance bottlenecks and optimization tools, such as critical rendering path optimization, resource loading optimization, and code optimization.
- Accessibility: Understand the WAI-ARIA standards and know how to build accessible web pages.
- Front-end system design: Design maintainable and scalable front-end architecture, component design, etc.
- Cross-browser compatibility: Understand the differences between different browsers and solutions.
Interview Questions :
1. Explain how the JavaScript Event Loop works.
2. How to optimize the loading speed of a web page? Please list a few ways.
3. Use pure JavaScript to implement a component, such as a modal box.
4. Explains the CSS Box Model and the difference between box-sizing: content-box and box-sizing: border-box.
5. Design an Autocomplete input box component.

MLE

Interviews for Machine Learning Engineers center on an understanding of machine learning theories, algorithms, models, and how they can be applied and deployed in the real world.

Examine the technical points:
- Machine Learning Foundations: Master the basic concepts of supervised learning, unsupervised learning, and reinforcement learning, and understand the principles of various classical algorithms (e.g., linear regression, logistic regression, support vector machines, decision trees, random forests, Boosting methods, clustering algorithms, etc.).
- Deep Learning: Familiar with neural network structure, forward propagation, backpropagation, loss functions, optimizers, and understanding of common deep learning models (CNN, RNN, Transformer, etc.).
- Data Processing and Feature Engineering: Familiarity with data cleaning, transformation, feature selection, and feature extraction techniques.
- Model Evaluation and Tuning: Knowledge of various evaluation metrics (accuracy, precision, recall, F1-score, AUC, etc.) and understanding of cross-validation, hyper-parameter tuning methods.
- Programming skills: Proficiency in Python with common machine learning libraries (e.g. NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).DSA and system design skills are equally important, especially when building ML systems.
- Probability and Statistics: Understand statistical concepts such as probability distributions, hypothesis testing, and Bayes' theorem.
Interview Questions:
1. Explain the tradeoffs between bias and variance, and how to diagnose and solve problems with high bias or high variance.
2. Describe the principles of gradient descent algorithms and explain the advantages and disadvantages of different variants (e.g., batch gradient descent, stochastic gradient descent, mini-batch gradient descent).
3. How do you evaluate the performance of a recommender system? Please list a few metrics.
4. Designing a system to detect fake news on the web.
5. Explain the principles and application scenarios of Principal Component Analysis (PCA).

DE

Interviews for data engineers focus on building, managing, and optimizing data pipelines, as well as mastery of large-scale data processing techniques.

Examine the technical points:
- SQL: Solid SQL skills to write complex queries, understand indexes, and optimize query performance.
- Data Modeling: Familiarity with data modeling for relational and non-relational databases, understanding of paradigm theory, star models, snowflake models, etc.
- ETL/ELT process: In-depth understanding of data extraction, transformation, and loading processes, and familiarity with related tools and techniques.
- Big Data Technology: Familiar with Hadoop ecosystem (HDFS, MapReduce), Spark, Kafka and other big data processing frameworks.
- Distributed Systems: Understand the fundamentals of distributed systems, consistency models, CAP theorem, etc.
- Programming skills: Proficiency in data processing and scripting using languages such as Python, Scala or Java.
- Data Warehouses and Data Lakes: Understand the concepts, architectures, and applicability scenarios of data warehouses and data lakes.
- Data Quality and Governance: Understand methods of measuring and assuring data quality.
Interview Questions :
1. Suppose you have a large dataset containing user behavioral events, how can you design a data model to store this data in order to efficiently query the user's behavioral path?
2. Write a SQL query to find the highest paid employee in each department.
3. Explain how MapReduce works.
4. How to design a scalable ETL pipeline that can handle terabytes of new data every day?
5. Explain the main differences between relational and NoSQL databases and the scenarios in which each is applicable.

Behavior Questions

Classic Behavioral Questions and Answer Ideas

Describe a project in which you solved a software engineering problem by combining innovative and standard approaches. Answer with a focus on explaining how you found a balance between creative solutions and established software development processes. Emphasize your decision-making process, the innovative approach you used, and how you combined it with software engineering standards to enhance project outcomes.

Tell us about an experience where your team has faced a major challenge. How did you contribute to solving the problem? Demonstrating your teamwork and problem-solving skills is critical. Detail the nature of the challenge, your role on the team, and the specific actions you took to find a solution. Highlight any unique technical or interpersonal skills you utilized.

Describe an experience where you had to learn a new skill in order to complete a project. How did you overcome the learning curve? This is designed to examine your ability to adapt and your enthusiasm for learning new skills. Explain the strategies you used to overcome your learning curve, such as online courses, mentorship, or trial-and-error methods, and how quickly you incorporated the new technology into your work.

Teamwork Behavior Questions and Answer Ideas

Describe an experience where you had to work closely with a team to solve a difficult technical problem. In your answer, clearly articulate the problem, your role on the team, your specific contribution to the solution, and the end result. Emphasize the technical skills and teamwork abilities you used.

Can you talk about a project experience where you had to integrate feedback from multiple teams, which may have included opinions that contradicted your personal views? Focus on demonstrating your communication and negotiation skills. Explain how you evaluated the feedback, integrated the different perspectives, and made a decision. Detail the outcome and what you gained from the experience.

Apple prides itself on innovation. Provide an example of a team project where you contributed an innovative solution. Discuss the context in which your innovative idea arose and how it influenced the team's approach to the project. Mention how the solution enhanced project outcomes and demonstrated alignment with Apple's commitment to innovation.

Role-Related Behavior Questions and Answer Ideas

Describe a project where you need to implement a software solution that has an in-depth consideration of user privacy. Answer by focusing on a privacy-centric approach, with special emphasis on your familiarity with local and global data protection regulations. Demonstrate your problem-solving skills and how you can bring your work in line with strict privacy standards like Apple's.

Tell me about an experience where you disagreed with a team member on a project. How did you handle the situation? Emphasize communication skills, the importance of teamwork, respect for differing opinions, and your approach to reaching consensus or compromise. Demonstrate your ability to work collaboratively in Apple's team-oriented culture.

Apple prides itself on innovation. Can you talk about an innovative solution you developed or contributed to in your past experience? Highlight an idea or innovative technology solution that you initiated or played a significant role in. Explain the impact of this innovation and how it fits into Apple's commitment to pushing the boundaries of technology and creating a seamless user experience.

Interview Prep

To prepare for an interview as a Software Engineer at Apple, candidates need to focus on knowledge and skills in the following areas: Core technologies, it is important to be proficient in Basic Data Structures and Algorithms (Basic DSA), Dynamic Programming, and Two Pointers, which are common programming problems, and in particular practice solving dynamic programming puzzles in a limited amount of time. In particular, you will need to practice solving dynamic programming problems in a limited amount of time. In addition, an understanding of Advanced Data Structures and Backtracking should be developed to deal with more complex problems that may arise. Interviews also emphasize problem solving and cultural fit, so prepare for behavioral interviews, which may cover your experience with technical problem solving, teamwork, conflict management, and possibly your understanding of innovation and approach to user privacy issues. Thorough preparation for both the technical knowledge and behavioral interviews is key to preparing for the Apple Software Engineer interview.

VO Interview Problem Solving Transcript

The interviewer gets right to the point and throws out questions: "Imagine we have a huge number of user files stored in iCloud Drive. Each file has a unique ID and a creation timestamp. Now, we need to show users a list of files sorted by their creation timestamps, but for privacy and data security reasons, we can't directly expose the original creation timestamps; instead, we need to show a hashed version. Can you please design an algorithm that can efficiently sort the list of files according to the hashed timestamp, while ensuring that files with earlier original creation timestamps also have their hashed timestamps as far forward as possible after sorting?"

The candidate heard the question and frowned slightly. Sorting the hashes directly obviously did not guarantee the relative order of the original timestamps, and it would defeat the purpose of privacy protection if the original timestamps were restored before sorting. His initial thought was to try to perform some sort of mathematical transformation on the hash to try to restore a portion of the ordering information of the original timestamps, but this was clearly futile. When he was at a standstill, the support team immediately pushed the idea of "custom comparators and stable sorting" - combining Apple's extreme pursuit of performance and privacy in data processing, we needed a way to satisfy the sorting requirements while taking into account the hash value's We need a way to satisfy both the sorting requirements and the hash value properties. We can take a stable sorting algorithm and provide it with a custom comparator. This comparator will determine the relative order of two hashed timestamps when comparing them by some rule (e.g., based on some feature of the hashes themselves, or by using the nature of the hashing algorithm to mimic the comparison behavior of the original timestamps as closely as possible without revealing the original information). The sub-device synchronization sends the Swift language code framework, highlighting the sort(by:) method and the use of custom closures:

				
					struct FileMetadata {
    let id: String
    let hashedTimestamp: Int // Assume the hashed timestamp is an integer
}

extension Array where Element == FileMetadata {
    mutating func sortFilesByHashedTimestamp() {
        self.sort { (file1, file2) -> Bool in
            // This is a schematic comparison logic that in practice needs to be carefully designed based on the hashing algorithm and business requirements.
            // The goal is to simulate the original timestamp sort as closely as possible without reverting to the original timestamps
            // For example, some bits of the hash can be compared, or the uniformity of the hash can be exploited
            // Suppose we design a hashing algorithm such that the higher bits of the hash reflect a portion of the temporal ordering information
            // The logic here is purely an example, the real world is much more complex and may involve multiple hashes, salting, etc.
            return file1.hashedTimestamp < file2.hashedTimestamp // example only, in reality it will be more complicated
        }
    }
}

// Example usage
var files: [FileMetadata] = [
    FileMetadata(id: "doc1", hashedTimestamp: 12345),
    FileMetadata(id: "doc2", hashedTimestamp: 12347),
    FileMetadata(id: "doc3", hashedTimestamp: 12340), FileMetadata(id: "doc3", hashedTimestamp: 12340)
]

files.sortFilesByHashedTimestamp()
print(files)</xmp

Taking our cue, the candidate immediately understood that the key was "stable sorting" and "custom comparators". He clearly explained how to use the sort(by:) method in Swift and emphasized the role of custom closures as comparators. He further explained that even if hashes are unordered, if we design a clever enough hashing algorithm and comparator, we can still bootstrap the sorting algorithm so that the result is as close to the order of the original timestamp as possible without exposing the original timestamp. He even mentioned that in the actual Apple system, it may be possible to combine the features of the hashing algorithm, for example, by introducing some time-related features in the hashing process, so that the hash value itself carries some ordering information, thus simplifying the design of the comparator. This kind of in-depth thinking about business scenarios and technical details successfully demonstrated solid skills from theoretical algorithms to engineering practice, and gained frequent nods from the interviewers.