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Apple

Machine Learning Engineer - Apple Store Online

Bengaluru, IndiaPosted 24 days ago

Apply on company site View full job

Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

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Imagine what you could do here! The people here at Apple don't just create products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.

Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. You will lead the way on our Online Retail Decision Automation team by researching and developing the next generation of algorithms used to drive the Apple Online experience! This role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimizing Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to be part of a new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers every day.

Description
To be successful, you need a strong machine learning background, proven software development skills, a love of learning, and to collaborate with cross-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to develop and implement machine learning algorithms. You'll mentor other MLE's and lead an effort to build scalable end-to-end machine learning solutions for our retail customers","responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment
Contribute to the ongoing improvement of our ML infrastructure and tooling
Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering
Ability to drive end to end solution collaborating with other MLEs and PMs
Ability to work in a fast pace hands on development organization

Preferred Qualifications
Experience building data processing pipelines and large scale machine learning platforms with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc
Experience operationalizing distributed applications
Experience building full stack applications for big data analysis, feature extraction and annotations

Minimum Qualifications
3+ years of related experience building high throughput scalable applications or building machine learning models
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems
Skilled in communication, problem solving, strategic thinking
Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience

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: Manufacturing

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