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.
Responsibilities
Search Architecture: Design, build, and maintain large-scale, low-latency, high-performance search systems that can scale. Build and optimize search and retrieval systems: Develop and optimize ranking, relevance, and retrieval through ML/AI models and merging traditional keyword search with vector-based semantic search using embedding models and vector databases. Query Understanding: Develop sophisticated NLP pipelines for intent classification, entity extraction, semantic parsing, and query expansion. Relevance & Ranking: Design and Implement machine learning models (e.g. Learning to Rank, Cross Encoder based models) and multi-stage reranking algorithms to optimize search precision and recall. Evaluation & Tuning: Build offline and online evaluation metrics, A/B testing frameworks, and continuous improvement strategies for search quality Collaborate cross-functionally: Partner with Research Scientists, Product, Data Engineering, MLOps, Search Infrastructure teams, and UX to align search features with business and user goals. Advance search research: Stay current with the latest research and innovations in search and information retrieval technologies, translating them into scalable production systems.
Minimum Qualifications
Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field 8+ years of experience in Machine Learning, Data Science, or Software Engineering roles with a significant focus on search infrastructure and information retrieval. Validated experience building and deploying large-scale search systems in production. Strong proficiency in C++, Go, Python or Java Deep familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost, etc.). Solid understanding of ML system design, model lifecycle, and experimentation pipelines. Extensive experience working with large datasets, data processing pipelines (e.g., Spark, Flink), and scalable architectures. Deep understanding of information retrieval, ranking algorithms, and user modeling techniques. Experience with real-time systems, user feedback loops, and model retraining pipelines. Vector Infrastructure: Hands-on experience with vector databases such as Milvus, Qdrant, Pinecone, or FAISS. Working knowledge of cloud environments (AWS or GCP) and containerization (Docker, Kubernetes) Experience building streaming platforms such as Apache Kafka or comparable message brokers Experience with search infrastructure such as OpenSearch, Elasticsearch, or similar search-based stacks 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. Strong foundation in deep learning architectures for search and retrieval (e.g., transformers, graph neural networks, learned sparse representations). Exposure to multi-objective optimization in search systems (e.g., relevance, diversity, freshness, fairness). Familiarity with MLOps tools and cloud platforms (AWS/GCP, MLflow, etc.) Experience with graph databases such as TigerGraph Experience with data and model versioning tools and practices (e.g., DVC, MLflow, Weights & Biases)
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 discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants
Apple accepts applications to this posting on an ongoing basis.