Machine Learning Engineer

Are you passionate about applying your deep understanding of machine learning technologies and data platform skills in creative ways? We at Apple's iCloud Mail team are searching for an excellent Machine Learning Engineer that can play a role in continuously innovating on iCloud Mail experience. The iCloud Mail engineering team is responsible for building groundbreaking infrastructure that supports our production mail service used by millions of users, sending billions of messages every day. The tasks include design, development, testing, deployment and support of mail infrastructure components passionate about customized mail experiences, anti-abuse, using big data, machine learning and artificial intelligence technologies.\\n

As a machine learning engineer, you will be focusing on: \n\nLeveraging existing AI/ML infrastructure, build new platform services and be responsible for building an end to end machine learning based product solution for improving iCloud Mail experiences.\n\nWorking with large volumes of data; extracting and manipulating large datasets using tools such as Spark SQL, command line and scripting languages.\n\nCollect ongoing qualitative and quantitative feedback from the user population and iterate based on the findings.\n\nBuilding high-performance, scalable and extensible REST based services for enhancing Mail consumer experience.\n\nDesign database schemas, write queries, and optimize database performance.\n\nConsider joining a small team writing the software which provides mail services to iCloud customers. We are looking for a very capable engineer who has a strong background in building high-performance, scalable and extensible systems using big data technologies. In addition to crafting efficient, testable, easy-to-maintain code, you recognize the importance of writing functional specifications and design documents. Quality is number one in your mind, and you flourish with building comprehensive unit and end-to-end tests, not only for features you build but also for existing features that need more testing. In this highly transparent position, the successful candidate will enhance existing mail systems while collaborating with multi-functional engineering teams, and also implement new customized mail experiences, in addition to preventing abuse of the system.\n

Deep understanding of predictive modeling and machine learning algorithms for supervised and unsupervised learning including classification, regression, clustering, etc.\n\nExcellent knowledge and experience in all major machine learning algorithms, statistical regression and deep learning included.\n\nStrong production experience training and evaluating ML models with accurate pipelines and metrics\n\nProficiency in working with distributed system, Hadoop, Spark, etc.\n\nProven programming skills, with proficiency in Python, Java, etc.\n\nProficient in design, implementation and maintenance of large-scale, high-performance mail real-time services and frameworks.\n\nProficient in Event-driven architecture and messaging frameworks (Pub/Sub, Kafka, and/or RabbitMQ)

Large Language Model training and Prompt engineering a big plus.