Machine Learning Engineer

Machine Learning Engineer

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

Description

APPLE INC has the following available 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. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $149,240 - $210,100/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: 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. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html.

Minimum Qualifications

Master's degree or foreign equivalent in Data Science, Computer Science or related field. Education and/or Experience must include:

• 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.
• Utilizing knowledge of search engines like Elasticsearch or Apache Solr to query information for API development.

Preferred Qualifications

N/A

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.