Machine Learning Engineer, Web Indexing Team

Santa Clara, California, United States$181,100 - $318,4007+ years

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish. Do you want to make Siri and Apple products smarter for our users? The MLPT & Infrastructure teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages, and Lookup. As part of this group, you will work within one of the most exciting high-performance computing environments, with petabytes of data and millions of queries per second, and have the opportunity to imagine and build products that delight our customers every single day.

We design and build infrastructures to support features that empower billions of Apple users through advanced intelligence systems. Our team processes trillions of links to find the best content to surface to users via search and other intelligent features. We also analyze pages to extract critical features for indexing, ranking, and retrieval. We apply statistical analysis to enhance link selection, content freshness, retrieval rates, and extraction quality, among many other aspects. Furthermore, we are building a generic Retrieval-Augmented Generation (RAG) indexing infrastructure framework to allow indexing building customization and support fast experiment iteration. You’ll have the opportunity to dive deeper into RAG systems, as well as large-scale data processing, managing trillions of records, petabytes of data, and the incredible complexity behind Apple Intelligence’s products.

Design, build, and scale infrastructure systems that support intelligent features powering billions of Apple users
Process and analyze trillions of links to surface the highest quality content across search and other intelligent features
Develop pipelines to extract critical features for indexing, ranking, and retrieval at massive scale
Apply statistical analysis to improve link selection, content freshness, retrieval rates, and extraction quality
Architect and contribute to a generic Retrieval-Augmented Generation (RAG) indexing infrastructure framework, enabling indexing customization and fast experimentation
Partner cross-functionally with machine learning, NLP, and product teams to deliver impactful, high-quality solutions
Mentor and provide technical guidance to junior engineers on the team

7+ years of software engineering experience, with a strong focus on large-scale distributed systems or infrastructure
Strong coding proficiency in one or more languages (e.g., Python, Java, Go, C++)
Solid foundation in computer science fundamentals including algorithms and data structures
Hands-on experience with large-scale data processing and MapReduce-style frameworks (e.g., Spark, Hadoop)
Experience with cloud services, particularly AWS (S3, EC2, EKS) and/or Kubernetes-based orchestration
Proven ability to operate independently and drive projects end-to-end in a collaborative team environment
MS or PhD in Computer Science or a related field, or equivalent practical experience

10+ years of software engineering experience, with demonstrated impact at a senior or staff level
Experience designing and building RAG systems or other AI/ML indexing pipelines
Background in machine learning, natural language processing, or information retrieval
Experience managing systems operating at petabyte scale with trillions of records
Strong communication skills with a track record of influencing technical direction across teams
MS or PhD in Computer Science or a related field, or equivalent practical experience

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 $181,100 and $318,400, 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.

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