AIML – Machine Learning Engineer, Machine Learning Platform & Infrastructure

Summary

Posted: Oct 16, 2024

Role Number:200573822

magine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish. Do you want to make Siri and Apple products smarter for our users? The Information Intelligence teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. As part of this group, you will work with one of the most exciting high performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day.

Description

We design and build infrastructures to support features that empowers billions of Apple users. Our team processes trillions of web links to select and crawl the most relevant content to surface to users through search. As part of the team, you’d be responsible for devising the algorithms to recommend most relevant urls for different search products, classifying the quality of the content and continuously deriving the signals from the content to enhance the system further. We apply statistical analysis to improve link selection, freshness, retrieval rates, extraction quality, and many others. We take full end-to-end ownership of our services, driving them through every stage meticulously, encompassing conception, design, implementation, deployment, and maintenance. As a result, each one of us takes our responsibilities seriously. In this team, you’ll have the opportunity to work on incredibly complex large scale systems with trillions of records and petabytes of data.

Minimum Qualifications

• MS or PhD in Computer Science or equivalent experience
• Strong coding skills and experience with data structures and algorithms
• Excellent interpersonal skills able to work independently as well as cross-functionally
• Experience with machine learning algorithms and tools
• Experience with petabyte scale data processing & building data pipelines
• Experience with AWS Services such as Amazon S3 EC2 EKS / Kubernetes

Preferred Qualifications

• Experience in statistics and data analysis.
• Experience with Machine Learning/Information Retrieval/Large Scale Data-Mining are a plus
• Experience in Web Crawling is a plus

Pay & Benefits

• At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $143,100 and $264,200, and your base pay will depend on your skills, qualifications, experience, and location.
  
  Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
  
  Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.