AIML - Staff Machine Learning Engineer - ML Platform & Technology

Apple

A leading technology company that designs, develops, and sells consumer electronics, software, and services.

Seattle, WA, USA

$166,600 - $296,300

Machine Learning

Staff Software Engineer

In-Person

5,000+ Employees

7+ years of experience

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Description For AIML - Staff Machine Learning Engineer - ML Platform & Technology

Join Apple's Machine Learning Platform team to build next-generation platforms for training deep learning models at scale. As a Staff Machine Learning Engineer, you'll be part of a team of distributed systems and ML experts, focusing on reliability, scalability, and performance of ML workloads. The role offers opportunities to work with world-class experts, contribute to cutting-edge AI technologies, and impact Apple's Intelligence products and services. You'll design and develop components for a centralized ML platform, optimize large-scale ML workloads, and have the chance to publish at top ML conferences. The position offers comprehensive benefits, competitive compensation ($166,600-$296,300), and the opportunity to work with state-of-the-art technology. Apple provides a respectful work environment, flexible responsibilities, and significant growth opportunities. The ideal candidate brings strong programming skills, distributed systems expertise, and deep learning experience, with 7+ years of industry experience. This role combines technical challenges with the opportunity to shape the future of AI at one of the world's most innovative companies.

Last updated 2 months ago

Responsibilities For AIML - Staff Machine Learning Engineer - ML Platform & Technology

Design and develop components for centralized, scalable ML platform
Push the limits of existing solutions for large-scale ML workloads
Develop novel techniques to circumvent limitations of existing solutions
Deploy techniques on high-impact tasks for Apple Intelligence products and services
Contribute to publishing work at top ML conferences and releasing open source contributions

Requirements For AIML - Staff Machine Learning Engineer - ML Platform & Technology

Python

Kubernetes

Kafka

Strong programming skills in Python or Go
Understanding of data structures, software design principles, and algorithms
Experience building large-scale distributed systems with tools such as Kubernetes, Kafka, Prometheus, etc.
Experience with deep learning frameworks, such as PyTorch, or JAX
Minimum of 7+ years of industry experience
Bachelors in the area of Computer Science or equivalent, or a related domain

Benefits For AIML - Staff Machine Learning Engineer - ML Platform & Technology

Medical Insurance

Dental Insurance

Education Budget

Equity

Relocation Benefits

Comprehensive medical and dental coverage
Retirement benefits
Employee stock programs
Educational expense reimbursement
Discretionary bonuses
Relocation assistance
Employee discount on products
Free services

Apple

A leading technology company that designs, develops, and sells consumer electronics, software, and services.

Seattle, WA, USA

$166,600 - $296,300

Machine Learning

Staff Software Engineer

In-Person

5,000+ Employees

7+ years of experience

Apple

Write a function using iteration to print numbers from 1 to a given number, then extend it to print only even numbers, and finally modify it to accept a step size.

Data Structures & AlgorithmsMedium

Write a function that uses iteration to print all numbers from 1 to a given number. For example, if the input is 5, the function should print: 1, 2, 3, 4, 5. Now, extend this function to print only the even numbers within that range. For instance, if the input is 10, the output should be: 2, 4, 6, 8, 10. Finally, modify the function to accept a second argument, which represents the step size. Using iteration, print numbers starting from 1 up to the given number, incrementing by the step size. As an example, given the number 15 and a step size of 3, the expected output is: 1, 4, 7, 10, 13. Be sure to handle edge cases and invalid inputs appropriately.

Arrays

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How would you design a platform architecture for a rapidly growing social media company to ensure scalability, reliability, performance, security, and cost-effectiveness?

System DesignMedium

Let's discuss platform architecture. Imagine you are tasked with designing a platform for a rapidly growing social media company. This platform needs to handle millions of users, support various media types (images, videos, text), and provide real-time updates. Consider the following: Scalability: How would you design the architecture to ensure it can handle increasing user traffic and data volume? Discuss specific technologies and strategies (e.g., load balancing, caching, sharding). Reliability: What measures would you take to ensure the platform remains available and fault-tolerant? Consider redundancy, monitoring, and disaster recovery. Performance: How would you optimize the platform for speed and responsiveness? Address concerns like database performance, content delivery, and API design. Security: What security considerations would you prioritize to protect user data and prevent attacks? Think about authentication, authorization, encryption, and vulnerability management. Cost: How would you balance performance, scalability, and reliability with cost-effectiveness? Discuss trade-offs and potential cost optimization strategies. Provide a high-level overview of your proposed architecture, including key components, technologies, and design principles. Explain your reasoning behind each choice and how it contributes to the overall goals of the platform. For example, would you choose a microservices architecture or a monolithic architecture? What type of database would you use and why? How would you handle real-time updates and notifications? What CDNs would you use?

Graphs

Dynamic Programming

Database Problems

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This question asks the candidate about their salary expectations. Interviewers ask this to see if the candidate's expectations align with the company's budget. It's crucial to research industry standards and company compensation ranges beforehand. Be prepared to discuss your desired salary range and how your skills and experience justify it. For example, you might say, "Based on my research and experience, I'm looking for a salary in the range of $X to $Y, but I am flexible."

Behavioral

What is your expected salary range?

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