Apple is looking to solve the problem of providing personalized content recommendations to millions of users worldwide by designing and developing personalization algorithms.
Requirements
- Utilizing backend programming languages such as Java, Python, and Scala, and frontend programming languages such as JavaScript, to work on multi-language codebases.
- Utilizing scalable datastore such as Cassandra, Redis and Voldemort for transactional data processing on the runtime services.
- Utilizing TensorFlow to develop and deploy deep learning model for runtime inference.
- Utilizing big data processing technology such as Spark, HDFS, Hive and Iceberg to develop large scale data pipeline.
- Utilizing Kafka to work on cross datacenter data sync and replications.
- Utilizing PySpark and PyTorch for Machine Learning.
- Utilizing Hibernate and Spring MVC frameworks to interact with SQL databases like MySQL or Postgres and NoSQL databases like Cassandra, MongoDB or similar.
Responsibilities
- Develop and refine algorithms that drive personalized content recommendations for millions of users worldwide.
- Utilize advanced machine learning techniques such as collaborative filtering, related model and deep to improve the accuracy and relevance of recommendations.
- Architect and implement scalable systems for real-time recommendation service and batch processing of large datasets.
- Build data pipelines using technologies like Apache Spark, Hive, and Kafka, and set up low-latency personalization Java runtime services utilizing technologies such as Apache Cassandra, Redis, Lucene and TensorFlow.
- Continuously explore new data sources and machine learning methods to refine recommendation models.
- Develop internal tools for prototyping and visualization of new algorithms.
- Design and conduct A/B tests to measure the impact of different personalization strategies on user engagement and satisfaction.
Other
- Master’s degree or foreign equivalent in Data Science, Computer Science or related field.
- 40 hours/week
- Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition.
- Eligible for discretionary bonuses or commission payments as well as relocation.
- Collaborate with product managers, researchers, and software developers to explore and evaluate new personalization strategies to integrate personalization into the broader product ecosystem.
