Senior Search Engineer - Services Special Projects

Role Number:
Team:
Software and Services

Location:

Cupertino Weekly

Hours:

40

Posted:
Summary 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.

Description 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.

Minimum Qualifications 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 to 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 FAISSFamiliarity with streaming platforms including Apache Kafka

Experience with search infrastructure including Open Search, 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

Preferred Qualifications 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 Tiger Graph 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, Torch Serve ) .Pay & Benefits 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 $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s…