Senior Engineering Manager, AI Search & Retrieval - Services Special Projects

Apple Inc.; San Francisco (CA); On-site; USD 238,000 - 402,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock programs

Relocation assistance

Tuition reimbursement

Job summary

Apple Inc. is seeking a Senior Engineering Manager for AI Search & Retrieval. You will own architecture for large-scale, low-latency search, guide retrieval and ranking across real-time, vector-based and hybrid methods, and lead a team of engineers who deliver the roadmap.

This hands-on leadership role blends technical vision with people leadership. You will drive evaluation, stay current with IR research, protect user privacy, and set guardrails for safe generative search results, collaborating

Qualifications

• We hold an MS in CS or equivalent; PhD is preferred.
• Note: this role requires 12+ years in ML, data science, or software with leadership.
• Requires leadership experience including hiring and mentoring senior engineers.
• Experience architecting large-scale search systems from design to production.
• Deep understanding of information retrieval, ranking algorithms, and user modeling.
• Experience with offline evaluation and online A/B testing for search relevance.
• Familiarity with vector databases and modern search stacks.
• Cloud, containerization (Docker/Kubernetes), and streaming platforms.

Responsibilities

• Set technical direction for large-scale, low-latency search infrastructure.
• Lead query understanding and retrieval strategy across pipelines and hybrid retrieval.
• Drive ranking strategy and AI/ML-driven search quality improvements.
• Own evaluation frameworks and A/B testing methodologies.
• Stay current with IR research and translate it to scalable designs.
• Ensure privacy as an architectural constraint in ranking and retrieval.
• Lead safety guardrails for generative AI outputs and red-teaming.
• Develop and ship AI-powered search features while improving developer productivity.
• Raise the technical bar through design reviews and coding standards.
• Represent the team in cross-functional design reviews with R&D, Product, Data Eng, MLOps, and Search Infra.
• Unblock high-risk technical problems and drive production delivery.
• Attract, hire, and mentor senior/staff engineers.
• Allocate work to roadmap with strong engineering discipline.
• Advocate for platform investments and communicate progress to leadership.
• Foster a culture of ownership, rigorous reviews, and user trust.

Skills

Leadership

Architectural design

Communication

Team mentoring

Systems programming (Go)

Java

Python

ML frameworks (TensorFlow/PyTorch)

Data processing pipelines (Spark/Flink

Education

MS in Computer Science

PhD preferred

Tools

Go

C++

Java

Python

Spark

Flink

OpenSearch/Elasticsearch

Milvus/Qdrant/Pinecone/FAISS

Job description

Senior Engineering Manager, AI Search & Retrieval - Services Special Projects

San Francisco Bay Area, California, United States Software and Services

We’re building a massive, real-time search experience that sits at the intersection of Generative AI and Information Retrieval! We make sense of high-volume structured and multimodal data and complex behavioral signals which deliver results that feel instant and relevant while still being private.Join our team as a ML Search Engineering Manager and take part in this rare opportunity to shape a user-facing product that millions of Apple customers rely on every day!

Description

We are looking for a Search Engineering Manager & Lead to serve as both the senior technicalauthority and the people leader for our search team. You'll own the architecture and long-term technical roadmap for large-scale, low-latency search infrastructure, from query understanding and hybrid retrieval through ranking and evaluation, and you'll also build, grow, and lead the team of search engineers who bring that roadmap to life.This is a hands-on leadership role with dual scope: you set the technical vision and personally shape the hardest retrieval and ranking decisions, and you also manage, mentor, and grow the engineers executing against it. Your leverage comes equally from what you design and from the team you build.

Responsibilities

• Set technical direction: own the architecture and long-term technical roadmap for large-scale, low-latency search infrastructure, making build-vs-buy and platform tradeoffs that the team executes against.
• Lead query understanding and retrieval strategy: guide the evolution of search pipelines, including autocomplete, query suggestions, and core search, intent classification, entity extraction, semantic parsing, and query expansion, and hybrid retrieval approaches spanning real-time, vector-based, and natural language search.
• Drive ranking strategy: set direction for relevance and ranking approaches (Learning to Rank, cross-encoder rerankers, multi-stage pipelines), driving AI/ML-powered search quality improvements that deliver measurable relevance gains, and review designs before they ship.
• Own evaluation rigor: drive the offline evaluation frameworks and online A/B testing methodology the team uses to validate search quality improvements.
• Track the state of the art: stay current with search and IR research, and translate promising techniques into scalable, production-ready designs for the team to build.
• Treat privacy as an architectural constraint: apply data minimization and privacy-preserving techniques to any user behavioral signal used in ranking or retrieval
• Own safety and trust for generative search results: set the guardrails against hallucination and harmful or misleading AI-generated answers, partnering with Trust & Safety on red-teaming and safety evaluation.
• Lead the development of generative AI-powered search features, and invest in developer productivity and tooling that let the team ship search capabilities faster.
• 2. Technical Leadership & Implementation (Lead scope)
• Raise the technical bar: lead design and code reviews, and establish the engineering standards and best practices the team builds against.
• Represent the team technically: act as the primary technical voice in cross-functional design reviews with Research Scientists, Product, Data Engineering, MLOps, and Search Infrastructure teams.
• Unblock the hardest problems: stay hands-on enough to jump into the most ambiguous or highest-risk technical problems, such as scaling bottlenecks, ranking regressions, or novel retrieval techniques, rather than delegating them away
• Drive the team's execution against the technical roadmap, from design through production delivery, and communicate progress, trade- offs, and risks to senior leadership and partner orgs.
• Partner with recruiting to attract, evaluate, and hire senior and staff search engineers, raising the technical bar with every hire.
• Manage a group of search engineers directly, owning their performance, career development, and technical growth, and mentor across levels on search and IR fundamentals, ranking, and retrieval systems.
• Allocate work against the roadmap, unblock execution, drive design reviews, and hold a high bar for engineering craft and operational excellence.
• Advocate for the investments the search platform needs, and communicate progress and risk to senior leadership and partner orgs.
• Cultivate a healthy engineering culture: high ownership, strong review practices, and a deep commitment to search quality and user trust.

Minimum Qualifications

• MS in Computer Science, Engineering, or a related technical field, or equivalent experience. PhD preferred.
• 12+ years of experience in Machine Learning, Data Science, or Software Engineering, with a significant focus on search infrastructure and information retrieval, including at least 5 years operating in a technical leadership or engineering management capacity
• Proven experience leading and managing engineers, including hiring, performance management, and technical mentorship of senior and staff ICs.
• Track record of leading the architecture of large-scale search systems from design through production.
• Deep understanding of information retrieval, ranking algorithms, and user modeling techniques.
• Experience designing offline evaluation frameworks and online A/B testing methodology to validate search relevance and ranking quality.
• Experience with vector databases (Milvus, Qdrant, Pinecone, or FAISS).
• Experience with search infrastructure such as OpenSearch, Elasticsearch, or similar stacks.
• Experience with cloud environments (AWS or GCP), containerization (Docker, Kubernetes), and streaming platforms (Kafka or comparable brokers).
• Excellent written and verbal communication, with the ability to align engineers, partner teams, and senior leadership around a shared technical direction.
• Strong proficiency in a systems language such as Go or C++, with working proficiency in Java or Python
• Deep familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost, or similar) and ML system design, model lifecycle, and experimentation pipelines.
• Extensive experience with large datasets, data processing pipelines (Spark, Flink), and scalable architectures.
• Working knowledge of data privacy principles (e.g., data minimization, privacy-preserving techniques) and experience applying them to systems that use user behavioral signals.
• Experience implementing safety guardrails for generative AI outputs, including hallucination mitigation, harmful-content filtering, and red-teaming or adversarial evaluation practices.

Preferred Qualifications

• Published work or patents in search systems, information retrieval, or related ML fields.
• Strong foundation in deep learning architectures for search and retrieval (transformers, graph neural networks, learned sparse representations).
• Exposure to multi-objective optimization in search (relevance, diversity, freshness, fairness).
• Track record of scaling engineering teams and modernizing infrastructure with measurable cost and reliability improvements.

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 $237,600 and $401,700, 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.