About this opportunity
Apple Inc. lists this Machine Learning Engineer Platform - iCloud Mail Intelligence opportunity in san diego, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
San Diego, California, United States Machine Learning and AI
Are you passionate about applying your deep understanding of machine learning technologies and data platform skills in creative ways? Apple's iCloud Mail Intelligence Platform team is looking for an excellent Machine Learning Engineer that can continuously innovate on the iCloud experience across Mail, Calendar, and Contacts. The team is responsible for building groundbreaking ML infrastructure that supports intelligent experiences for hundreds of millions of users worldwide.
Description
Consider joining a team that brings intelligent experiences to Mail, Calendar, and Contacts for millions of iCloud customers. Quality and user privacy are central to everything we build. We are looking for an experienced ML engineer who has a strong background in building high-performance, scalable, and extensible systems using big data, machine learning, and artificial intelligence technologies. You recognize the importance of writing functional specifications and collaborating on high-level design documents. You craft efficient, well-documented code with comprehensive unit and end-to-end tests. The successful candidate will demonstrate an ability to collaborate with multi-functional engineering teams to expand ML infrastructure capabilities and build ML-driven experiences across Mail, Calendar, and Contacts. You will leverage existing AI/ML infrastructure and contribute to building new platform services that accelerate machine learning development. You will also design, build, and deploy ML models and features that improve the iCloud experience for millions of users.
Responsibilities
Standardize and accelerate ML feature development across Mail, Calendar, and Contacts
Design, develop, and deploy end-to-end machine learning applications and models that improve the iCloud experience
Work with large volumes of data; extract and manipulate large datasets using tools such as Spark, SQL, command line, and scripting languages
Build high-performance, scalable, and extensible services for delivering ML models and features into production
Establish and apply standards for evaluation, testing, and model observability
Collect ongoing qualitative and quantitative feedback from the user population and iterate based on the findings
Partner with multi-functional engineering teams to enhance existing systems and implement new ML-driven experiences across Mail, Calendar, and Contacts
Minimum Qualifications
Strong production experience training, evaluating, and operating ML models with end-to-end ML pipelines: data processing, feature engineering, training, serving, and monitoring
Experience with large-scale distributed systems including data processing, event-driven architectures and both real-time and batch inference
Strong programming skills in one or more production languages (e.g., Python, Java, Scala, Kotlin, Go)
Demonstrated ability to drive projects independently from problem definition to production
Deep understanding of predictive modeling and machine learning algorithms across supervised and unsupervised learning
Preferred Qualifications
5+ years of ML engineering experience (or equivalent depth) with a track record of technical leadership on large-scale ML systems or ML platforms that standardize workflows across multiple teams
Experience with agent-based architectures, orchestration frameworks, and LLM observability and evaluation tooling
Expertise with LLMs, including fine-tuning, prompt engineering, embeddings, retrieval systems, evaluation, and integration into production systems
Experience deploying models across multiple runtimes (e.g., on-device, server-side)
Understanding of privacy-preserving ML techniques and responsible data handling
Familiarity with email, calendar, or contacts domains, or other communications and productivity systems
MS/PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
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 $175,000 and $263,300, 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.
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.
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace.
Learn about reasonable accommodations for job applicants.
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Worksite address
san diego, CA, 92189, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.