Senior Search Engineer - Services Special Projects

Apple • Cupertino, CA

12d

About The Position

The team is building a large-scale, real-time search experience combining Generative AI and Information Retrieval. The Senior Search Engineer will design, develop, and optimize large-scale search systems and help shape a product intended to serve millions of users.

This role is suited to a technically deep engineer with product sense who enjoys solving real-world problems using modern AI models and scalable systems. The engineer will work closely with AI/ML scientists and engineers to create intelligent systems that personalize user experiences.

Requirements

• 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 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, such as transformers, cross-encoder models, graph neural networks, and learned sparse representations.
• Experience with multi-objective optimization in search systems, such as relevance, diversity, freshness, and fairness.
• 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, including AWS, and containerization tools such as Docker and Kubernetes.
• Extensive experience 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 directly in production query/request paths.
• Past successful model deployments, including tuning models through techniques such as quantization for performance and quality optimization.
• Excellent communication skills and a collaborative mindset.

Nice To Haves

• Master's degree; PhD preferred.
• Published work or patents in search systems, information retrieval, or related ML fields.
• Experience with graph databases such as TigerGraph.
• Experience with data and model versioning tools and practices, such as DVC, MLflow, and Weights & Biases.
• Deep experience with key-value stores, including SSTables and Cassandra.
• Experience tuning KV-cache and batching for low-latency, high-throughput real-time inference.
• Deep production-level experience with inference runtimes and compilers such as ONNX Runtime and TensorRT/TensorRT-LLM, and serving frameworks such as vLLM, SGLang, Triton, or TorchServe.

Responsibilities

• Design, develop, and optimize large-scale search systems.
• Build and deploy production search systems at scale.
• Work with AI/ML scientists and engineers at the intersection of Generative AI and Information Retrieval.
• Craft intelligent systems that personalize user experiences.
• Deploy, serve, and optimize LLMs, embeddings, and ML models in production query/request paths.
• Tune models, including quantization, to optimize performance and quality.

What This Job Offers

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