Machine Learning Engineer Platform - iCloud Mail Intelligence

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.

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