February 22, 2025

Applied Machine Learning Engineer - Customer Feedback

Mid • On-site

$143,100 - $264,200/yr

Cupertino, CA

Summary

Posted:
Weekly Hours: 40
Role Number:200578047
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

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.

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.

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.