Machine Learning Engineer Platform iCloud Mail Intelligence

Are you passionate about applying your deep understanding of machine learning technologiesnand data platform skills in creative ways Apples iCloud Mail Intelligence Platform team isnlooking for an excellent Machine Learning Engineer that can continuously innovate on theniCloud experience across Mail Calendar and Contacts. nnThe team is responsible for building groundbreaking ML infrastructure that supports intelligent experiences for hundreds of millionsnof users worldwide.n

Consider joining a team that brings intelligent experiences to Mail Calendar and Contacts fornmillions of iCloud customers. Quality and user privacy are central to everything we are looking for an experienced ML engineer who has a strong background in building high-nperformance scalable and extensible systems using big data machine learning and artificialnintelligence technologies. You recognize the importance of writing functional specifications andncollaborating on high-level design documents. You craft efficient well-documented code withncomprehensive unit and end-to-end successful candidate will demonstrate an ability to collaborate with multi-functionalnengineering teams to expand ML infrastructure capabilities and build ML-driven experiencesnacross Mail Calendar and Contacts. You will leverage existing AI/ML infrastructure andncontribute to building new platform services that accelerate machine learning will also design build and deploy ML models and features that improve the iCloudnexperience for millions of users.

Standardize and accelerate ML feature development across Mail Calendar and ContactsnnDesign develop and deploy end-to-end machine learning applications and models that improve the iCloud experiencennWork with large volumes of data; extract and manipulate large datasets using tools such as Spark SQL command line and scripting languagesnnBuild high-performance scalable and extensible services for delivering ML models and features into productionnnEstablish and apply standards for evaluation testing and model observabilitynnCollect ongoing qualitative and quantitative feedback from the user population and iterate based on the findingsnnPartner with multi-functional engineering teams to enhance existing systems and implement new ML-driven experiences across Mail Calendar and Contactsn

Strong production experience training evaluating and operating ML models with end-to-end ML pipelines: data processing feature engineering training serving and monitoringnnExperience with large-scale distributed systems including data processing event-driven architectures and both real-time and batch inferencennStrong programming skills in one or more production languages (e.g. Python Java Scala Kotlin Go)nnDemonstrated ability to drive projects independently from problem definition to productionnnDeep understanding of predictive modeling and machine learning algorithms across supervised and unsupervised learning

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 teamsnnExperience with agent-based architectures orchestration frameworks and LLM observability and evaluation toolingnnExpertise with LLMs including fine-tuning prompt engineering embeddings retrieval systems evaluation and integration into production systemsnnExperience deploying models across multiple runtimes (e.g. on-device server-side)nnUnderstanding of privacy-preserving ML techniques and responsible data handlingnnFamiliarity with email calendar or contacts domains or other communications and productivity systemsnnMS/PhD in Computer Science Machine Learning or a related technical field or equivalent practical experience