Machine Learning Engineer

Apple • San Diego, CA

31d

About The Position

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.

As a machine learning engineer, you will be focusing on: Leveraging 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. Working with large volumes of data; extracting and manipulating large datasets using tools such as Spark SQL, command line and scripting languages. Collect ongoing qualitative and quantitative feedback from the user population and iterate based on the findings. Building high-performance, scalable and extensible REST based services for enhancing Mail consumer experience. Design database schemas, write queries, and optimize database performance. Consider 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.

Requirements

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

Nice To Haves

• Large Language Model training and Prompt engineering a big plus

Responsibilities

• Leveraging existing AI/ML infrastructure, build new platform services
• Building an end to end machine learning based product solution for improving iCloud Mail experiences
• Working with large volumes of data; extracting and manipulating large datasets using tools such as Spark SQL, command line and scripting languages
• Collect ongoing qualitative and quantitative feedback from the user population and iterate based on the findings
• Building high-performance, scalable and extensible REST based services for enhancing Mail consumer experience
• Design database schemas, write queries, and optimize database performance
• Enhance existing mail systems while collaborating with multi-functional engineering teams
• Implement new customized mail experiences
• Preventing abuse of the system

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed