The role of Search Systems Engineer involves designing, developing, and optimizing large-scale search systems that integrate Generative AI and Information Retrieval. This position is part of a passionate team focused on creating a real-time search experience for users at Apple scale. The ideal candidate will have a strong technical background and a product-oriented mindset, working closely with AI/ML scientists and engineers. This is a unique opportunity to shape a product that millions will rely on.

• Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related field
• 10+ years of experience in Machine Learning, Data Science, or Software Engineering roles with a significant focus on search infrastructure and information retrieval
• Hands-on experience building and deploying large-scale search systems in production
• Deep understanding of information retrieval, query understanding, query augmentation, and multi-stage ranking algorithms
• Strong foundation in deep learning architectures for search and retrieval
• Experience with multi-objective optimization in search systems
• Experience with real-time systems, user feedback loops, and model retraining pipelines
• Strong proficiency in Go, Java, C++, and Python
• Proven experience with ML frameworks including PyTorch and XGBoost
• Familiarity with cloud environments and containerization
• Extensive experience working with data processing pipelines including Spark and Flink
• Hands-on experience with vector search including FAISS
• Familiarity with streaming platforms including Apache Kafka
• Experience with search infrastructure including OpenSearch and/or Elasticsearch
• Hands-on experience deploying, serving, and optimizing LLMs, embeddings, and ML models in production
• Past successful deployments with tuning of models for performance and quality optimization
• Excellent communication skills and a collaborative mindset
• Master's Degree; PhD Preferred
• Published work or patents in the domain of search systems or related ML fields
• Experience with graph databases such as TigerGraph
• Experience with data and model versioning tools and practices
• Deep experience with KV Stores including SSTables and Cassandra
• Experience with tuning KV-cache and batching for low-latency, high-throughput real-time inference
• Deep production level experience with inference runtimes and serving frameworks

• Design and develop large-scale search systems that leverage Generative AI and Information Retrieval.
• Collaborate with AI/ML scientists and engineers to craft intelligent systems that enhance user experiences.
• Optimize search infrastructure for performance and scalability.
• Implement multi-objective optimization strategies in search systems.
• Deploy and serve machine learning models directly in the production query/request path.
• Tune models for performance and quality optimization.
• Work with data processing pipelines and real-time systems to ensure efficient model retraining.
• Communicate effectively with team members and stakeholders to drive project success.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.