Machine Learning Engineer

Apple • Seattle, WA

2h

About The Position

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. 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 setting 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. This involves full-stack web development utilizing frontend and backend languages such as JavaScript and Java. 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. 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. 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 $212,202 - $258,100/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. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Requirements

• Master’s degree or foreign equivalent in Management Information Systems, Computer Science, Information Technology, Software Engineering, or a related field and 5 years of experience in the job offered or related occupation.
• 2 years of experience with each of the following skills is required: Utilizing Java, Scala and JavaScript to work on multi-language codebases.
• Utilizing TensorFlow to develop and deploy deep learning model for runtime inference.
• Utilizing big data processing technology including Spark, HDFS, Hive and Iceberg to develop large scale data pipeline.
• Utilizing Hibernate and Spring MVC frameworks to interact with SQL databases like MySQL or Postgres and NoSQL databases (Cassandra, MongoDB or similar).
• Utilizing knowledge of search engines including Elasticsearch or Apache Solr to query information for API development.
• Building foundations of a micro-services-based personalization systems.
• Maintaining and iteratively improving the recommender systems that connect users to the right content utilizing large-scale Python, Scala, Spark based pipelines
• Collaborate with data scientists on developing features, prototyping, and iterative tuning of recommendation models
• Helping to maintain the data processing workflows utlizing Airflow and Redshift feeding personalization and Business Intelligence system
• Monitoring performance and usability of data systems, ensuring that SLOs are met

Nice To Haves

• N/A

Responsibilities

• 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.
• 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 setting 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. This involves full-stack web development utilizing frontend and backend languages such as JavaScript and Java.
• 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.
• 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.
• 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.

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.
• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• For formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition.
• This role might be eligible for discretionary bonuses or commission payments as well as relocation.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level