Machine Learning/ Search Engineer - Services Special Projects

Apple • Cupertino, CA

7d

About The Position

Our team is building a massive, real-time search experience from the ground up — one that will reach users at Apple scale. It's search at the intersection of Generative AI and Information Retrieval, and it's a rare opportunity to shape a product that millions will rely on. We are seeking a highly experienced and innovative Search Systems Engineer to help design, develop, and optimize large-scale search systems. This role is ideal for a technically deep individual who has a strong product sense and enjoys solving real-world problems using modern AI models and scalable systems. We are a passionate team of hardworking engineers and scientists, and we are looking for a strong Search engineer to join us. You will work closely with AI/ML Scientists and engineers at the intersection of Generative AI and Information Retrieval, crafting 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 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 (e.g., transformers, cross encoder models, graph neural networks, learned sparse representations).
• Experience with multi-objective optimization in search systems (e.g., relevance, diversity, freshness, 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, XGBoost.
• Familiarity with cloud environments (including AWS) and containerization (Docker, Kubernetes)
• Extensive experience working with data processing pipelines including Spark, 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 the production query/request path
• Past successful deployments with tuning of models (including 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 the domain of search systems, information retrieval, or related ML fields.
• Experience with graph databases such as TigerGraph
• Experience with data and model versioning tools and practices (e.g., DVC, MLflow, Weights & Biases)
• 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/compilers (ONNX Runtime, TensorRT/TensorRT-LLM), and serving frameworks (vLLM, SGLang or Triton, TorchServe ) .

Responsibilities

• Design, develop, and optimize large-scale search systems.
• Work closely with AI/ML Scientists and engineers at the intersection of Generative AI and Information Retrieval.
• Craft intelligent systems that personalize user experiences.
• Build and deploy large-scale search systems in production.
• Implement real-time systems, user feedback loops, and model retraining pipelines.
• Deploy, serve, and optimize LLMs, Embeddings and ML models directly in the production query/request path.
• Tune models (including quantization) for performance and quality optimization.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree