Machine Learning Engineer - Apple Store Online
Apple
Machine Learning Engineer - Apple Store Online
Job Description
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. 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
Locations
- Bengaluru, Karnataka, India 560001
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,500,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- machine learning backgroundintermediate
- software development skillsintermediate
- developing models for product searchintermediate
- recommendation systemsintermediate
- rankingintermediate
- page generationintermediate
- personalizationintermediate
- evidenceintermediate
- messagingintermediate
- marketingintermediate
- Generative AIintermediate
- optimizing systems & infrastructureintermediate
- collaborate with cross-functional teamsintermediate
- develop and implement machine learning algorithmsintermediate
- mentor other MLE’sintermediate
- build scalable end-to-end machine learning solutionsintermediate
Required Qualifications
- 7+ years of related experience building high throughput scalable applications or building machine learning models (experience, 7 years)
- Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems (experience)
- Skilled in communication, problem solving, strategic thinking (experience)
- Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience (experience)
Preferred Qualifications
- Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience (experience)
- Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture (experience)
- Experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc) (experience)
- Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems (experience)
Responsibilities
- 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
- Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment
- Provide mentorship and guidance to other machine learning engineers and staying up-to-date with the latest advances in machine learning and software engineering
- Contribute to the ongoing improvement of our ML infrastructure and tooling, ensuring that we stay at the cutting edge of industry practices.
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Machine Learning Engineer - Apple Store Online
Apple
Machine Learning Engineer - Apple Store Online
Job Description
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. 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
Locations
- Bengaluru, Karnataka, India 560001
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,500,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- machine learning backgroundintermediate
- software development skillsintermediate
- developing models for product searchintermediate
- recommendation systemsintermediate
- rankingintermediate
- page generationintermediate
- personalizationintermediate
- evidenceintermediate
- messagingintermediate
- marketingintermediate
- Generative AIintermediate
- optimizing systems & infrastructureintermediate
- collaborate with cross-functional teamsintermediate
- develop and implement machine learning algorithmsintermediate
- mentor other MLE’sintermediate
- build scalable end-to-end machine learning solutionsintermediate
Required Qualifications
- 7+ years of related experience building high throughput scalable applications or building machine learning models (experience, 7 years)
- Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems (experience)
- Skilled in communication, problem solving, strategic thinking (experience)
- Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience (experience)
Preferred Qualifications
- Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience (experience)
- Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture (experience)
- Experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc) (experience)
- Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems (experience)
Responsibilities
- 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
- Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment
- Provide mentorship and guidance to other machine learning engineers and staying up-to-date with the latest advances in machine learning and software engineering
- Contribute to the ongoing improvement of our ML infrastructure and tooling, ensuring that we stay at the cutting edge of industry practices.
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Engineer - Apple Store Online @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs