Machine Learning Engineer [req#200617047]

Machine Learning Engineer

Apple Inc has the following available for Machine Learning Engineer in Seattle, Washington. Design and Develop Personalization Algorithms: 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. System Architecture and Implementation: Architect and implement scalable systems for real-time recommendation service and batch processing of large datasets. This involves building data pipelines using technologies like Apache Spark, Hive, and Kafka, and setting up low-latency personalization Java runtime services utilizing technologies such as Apache Cassandra, Redis, Lucene and TensorFlow. Prototyping and Innovation: Continuously explore new data sources and machine learning methods to refine recommendation models. Develop internal tools for prototyping and visualization of new algorithms. This involves full-stack web development utilizing frontend and backend languages such as JavaScript and Java. Experimentation and Testing: Design and conduct A/B tests to measure the impact of different personalization strategies on user engagement and satisfaction. Analyze experiment results and integrate successful features into production systems. Production Deployment and Maintenance: Deploy personalization runtime algorithms and offline data pipelines into production environments, ensuring robustness and scalability. Monitor system performance and health, performing regular maintenance and updates as needed. Cross-Functional Collaboration: Collaborate with product managers, researchers, and software developers to explore and evaluate new personalization strategies to integrate personalization into the broader product ecosystem. Provide expertise on machine learning and personalization to guide product development and strategic decisions. $149,240 - $210,100/yr.

Requirements: Master's degree or foreign equivalent in Data Science, Computer Science or related field. Education and/or Experience must include: 1. Utilizing backend programming languages such as Java, Python, and Scala, and frontend programming languages such as JavaScript, to work on multi-language codebases. 2. Utilizing scalable datastore such as Cassandra, Redis and Voldemort for transactional data processing on the runtime services. 3. Utilizing TensorFlow to develop and deploy deep learning model for runtime inference. 4. Utilizing big data processing technology such as Spark, HDFS, Hive and Iceberg to develop large scale data pipeline. 5. Utilizing Kafka to work on cross datacenter data sync and replications. 6. Utilizing PySpark and PyTorch for Machine Learning. 7. Utilizing Hibernate and Spring MVC frameworks to interact with SQL databases like MySQL or Postgres and NoSQL databases like Cassandra, MongoDB or similar. 8. Utilizing knowledge of search engines like Elasticsearch or Apache Solr to query information for API development.