Machine Learning Engineer

Apple News is hiring a Machine Learning Engineer to help build and scale the infrastructure behind machine learning powered product features. The role in Cupertino supports production model serving and deployment workflows, along with monitoring, data pipelines, and improvements to content tagging, ranking, clustering, and personalization.

What you’ll do

• Build and maintain infrastructure for hosting and serving both classical ML models (such as gradient boosting and SVMs) and deep learning models (including transformers and neural rankers) with a focus on latency, reliability, and scalability
• Evaluate tools and frameworks for model serving and feature delivery, including Kubernetes, Spark, Cassandra, Solr, Spring Boot, AWS, and GCP, learning how trade-offs affect cost, scalability, reliability, and latency
• Partner with model development teams to contribute to a shared codebase, develop common data processing libraries, and profile or optimize ML workloads
• Create reusable pipeline infrastructure for training data workflows, including sampling and collecting data, plus labeling using human annotations or LLMs
• Design and implement model monitoring, observability, and alerting systems to support production reliability and performance SLAs
• Analyze real world user interaction data with guidance from senior teammates to identify training distribution gaps and define model success metrics

Required qualifications

• MS in Computer Science, Machine Learning, or a related discipline, or equivalent work experience in this domain
• 2+ years of industry experience in machine learning infrastructure or software engineering with exposure to ML systems
• Strong proficiency in Java and/or Python, with interest in production serving systems
• Experience contributing to or building ML infrastructure such as model serving, deployment pipelines, or feature delivery systems
• Some experience deploying ML models on AWS and/or GCP, along with a developing understanding of deployment trade-offs across latency, cost, and scalability
• Good cross-functional communication skills, including the ability to explain technical concepts clearly

Helpful experience

• Familiarity with RAG concepts such as retrieval, embedding, chunking, or reranking
• Experience building or contributing to data pipelines for A/B test analysis or training dataset creation using Apache Spark
• Interest in content personalization or recommendation systems at consumer scale
• Experience contributing to AI powered features with measurable impact on user engagement or content quality

Additional preferred areas

• Familiarity with inference optimization methods such as quantization, batching, caching, and model distillation
• Exposure to embedding pipeline infrastructure or vector store concepts including indexing strategies, approximate nearest neighbor search, and latency versus recall trade-offs

Technologies

• Java, Python
• Kubernetes, Spark, Cassandra, Solr, Spring Boot
• AWS, GCP
• RAG (retrieval, embedding, chunking, reranking), LLMs
• Gradient boosting, SVMs, transformers, neural rankers
• A/B test analysis
• Apache Spark

Pay and benefits

The base pay range for this role is USD 150,400 - 225,300 per year, depending on skills, qualifications, experience, and location. Apple benefits and compensation programs are subject to eligibility requirements and the terms of the applicable plan or program.

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Opportunity to become an Apple shareholder through Apple’s discretionary employee stock programs
• Eligible for discretionary restricted stock unit awards
• Ability to purchase Apple stock at a discount via participation in the Employee Stock Purchase Plan
• May be eligible for discretionary bonuses or commission payments and relocation

Location: Cupertino, CA (onsite)