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Apple

Sr Machine Learning Engineer, Proactive - ML Systems Engineering

Cupertino, CA$150,400 – $277,600Posted 25 days ago

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Apple's products combine the best hardware and incredible software to deliver magical experiences to our customers. The Proactive Intelligence team builds features that anticipate customer's needs and create personalized experiences by adapting to user behaviors with machine learning running locally on users' devices. We are seeking exceptional software engineers with a strong machine learning background to join our team where we're making Apple Intelligence more capable and personalized to surprise and delight our millions of customers on the iPhone, Mac, Apple Watch, iPad, and more!

Description

We are seeking passionate, creative, and curious engineers with experience shipping machine learning systems and a proven track record of outstanding software engineering abilities. We need your expertise to invent the future by integrating new features with highly complex systems. You will need to learn and deeply understand the way Apple's software operates in order to deliver new capabilities and features. The most successful engineers ask questions, are eager to teach and learn together, and share a common belief that that we can surprise and delight our customers with personalized intelligent experiences in all of Apple's products. Join us to benefit the lives of hundreds of millions of people around the world!","responsibilities":"As a member of our team, you will ship excellent software for machine learning systems; establish scalable automated processes for evaluation and monitoring; contribute to a healthy team culture where everyone feels respected, empowered, and challenged to grow; commit to engineering excellence by upholding best practices that enable us to move quickly with confidence; obsess over the user experience first, and learn the power of story telling to communicate complex ideas; and develop innovative tools and techniques that change the way we look at problems. Join the Proactive Intelligence team to create the future of intelligent experiences across our entire lineup of devices iPhone, iPad, HomePod, Mac, Apple Watch, AppleTV, and more!

Preferred Qualifications

Experience working with ML pipelines and large datasets in production environments

Experience in resource constrained computing (e.g., embedded systems or mobile development)

Minimum Qualifications

3+ years of experience building production machine learning systems

Proficiency in Python programming

Proficiency in at least one compiled language like C, C++, Objective-C, Swift, Go, Java, Kotlin, C#, or Rust

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 $150,400 and $277,600, 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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology

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