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Home›Jobs›Apple›Applied Machine Learning Engineer - Customer Feedback
Apple

About Apple

The personal technology company redefining user experience

🏢 Tech, Hardware👥 1001+ employees📅 Founded 1976📍 Cupertino, CA⭐ 4.2
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Key Highlights

  • Market cap of $3 trillion as of 2022
  • Over 1 billion active devices worldwide
  • Comprehensive medical plans including mental healthcare
  • Paid parental leave and gradual return-to-work program

Apple Inc. (NASDAQ: AAPL), headquartered in Cupertino, CA, is the world's most valuable company with a market capitalization of $3 trillion as of 2022. Known for its iconic products such as the iPhone, iPad, and Mac, Apple serves over 1 billion active devices globally. The company has a strong commi...

🎁 Benefits

Apple offers comprehensive medical plans covering physical and mental healthcare, paid parental leave, and a gradual return-to-work program. Employees...

🌟 Culture

Apple's culture emphasizes an obsessive focus on user experience and consumer privacy, setting it apart from competitors. The company promotes inclusi...

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Apple

Applied Machine Learning Engineer - Customer Feedback

Apple • Cupertino, California, United States

Posted 10 months ago🏛️ On-SiteMid-LevelMachine learning engineer📍 Cupertino
Apply Now →

Job Description

Join the team responsible for Apple’s Feedback and Beta Programs! Our tools and applications collect user feedback on beta software releases, helping to drive the direction and priorities of Apple’s engineering teams. To make the best use of feedback we receive from customers and developers, we develop and maintain machine learning systems and automated analysis to cluster, annotate, and escalate the millions of reports we receive yearly. We are looking for experienced Machine Learning engineers to deploy and tune both traditional ML and generative AI models to enhance our systems’ capability. There are tantalizing problems and products possible with our one-of-a-kind dataset, and plenty of opportunity for a passionate engineer.

Description

Our team is seeking adept machine learning engineers who are excited by creating machine-learning-driven user experiences. Work includes implenting high-performance machine learning models and infrastructure in concert with software engineers, designers, and teams of internal users. You will be responsible for full stack ML development in partnership with others on the team. This includes data generation and curation, creating and influencing ML tooling and infrastructure, driving evaluation efforts, and training or fine-tuning models. You will also be involved in directly integrating ML into internal tools and systems. You will need to rely on your creativity and problem solving to develop scalable, maintainable, and cost-effective solutions. The team values rapid iteration, based on bringing models into reality so stakeholders can play with cutting edge technology and research. To this end you will be engaged with hardware, software, and design teams across Apple; both representing the technology and implementing it into prototypes. You will be successful and feel fulfilled in our team if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.

Minimum Qualifications

Industry experience with applied machine learning. Industry experience in software engineering, data engineering, or similar. Strong fundamentals in problem solving, algorithm design, and model building Excellent verbal and written communication and presentation skills MS in Computer Science or related experience

Preferred Qualifications

Working knowledge of applied Natural Language Processing. Strong hands-on experience in building large scale ML based solutions or in building and scaling distributed systems.

Eeo Content

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

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