This role pays less than
58%
of similar roles. Most pay
$196,350–$254,750
— the shaded band above.
At the midpoint, this role pays about
$219k
versus about
$226k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
The Machine Learning Engineer Platform - iCloud Mail Intelligence role sits within the iCloud Mail Intelligence Platform team, where you will develop infrastructure and features for Mail, Calendar, and Contacts. You will design, build, and deploy end-to-end machine learning applications, standardize feature development across multiple products, and establish standards for model observability and testing. Your daily work involves managing large volumes of data to create high-performance, scalable services that deliver models into production. To succeed, you must be proficient in Python, Java, Scala, Kotlin, or Go, while utilizing Spark, SQL, and command-line tools. The role requires expertise in predictive modeling, supervised and unsupervised learning, and LLM technologies including fine-tuning and prompt engineering. You will solve complex problems related to large-scale distributed systems, real-time inference, and privacy-preserving machine learning techniques within the communications and productivity domain.
Design, develop, and deploy end-to-end machine learning models and features to improve the iCloud experience.
Build high-performance, scalable, and extensible services for delivering ML models into production environments.
Extract and manipulate large datasets using tools such as Spark, SQL, and various scripting languages.
Standardize and accelerate ML feature development across Mail, Calendar, and Contacts platforms.
Establish and apply standards for model evaluation, testing, and observability.
Develop new platform services to accelerate machine learning development and infrastructure capabilities.
Collect and analyze qualitative and quantitative user feedback to iterate on product features.
What we're looking for
Experience training, evaluating, and operating ML models with end-to-end pipelines including data processing, feature engineering, serving, and monitoring.
Experience with large-scale distributed systems involving event-driven architectures and real-time or batch inference.
Strong programming skills in production languages such as Python, Java, Scala, Kotlin, or Go.
Deep understanding of predictive modeling and machine learning algorithms across supervised and unsupervised learning.
Ability to drive projects independently from problem definition through to production.
5+ years of ML engineering experience with a track record of technical leadership on large-scale ML systems or platforms.
Expertise with LLMs, including fine-tuning, prompt engineering, embeddings, retrieval systems, and integration into production.
MS/PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
Machine Learning
LLMs
Python
Java
Scala
Kotlin
Go
Spark
SQL
Distributed Systems
Prompt Engineering
Retrieval Systems
Feature Engineering
Model Observability
Batch Inference
Data Processing
Machine Learning
Generative AI
Python
C++
Deep Learning Frameworks
Time-series Analysis
SoC Architecture
Silicon
Feature Engineering
System Architecture