Job Details

Machine Learning Engineer, AI/ML Search Platform, Apple Services Engineering

Seattle, Washington, United States

Software and Services

Summary

Posted: Sep 03, 2025

Weekly Hours: 40

Role Number: 200616648-3337

Are you a passionate about building scalable, reliable, search platform at scale? Come join us and be part of the Apple Media Products incredible journey. Apple Media Search Platform team is looking for extraordinary search engineers to build the best music search experience across all Apple platforms. We are a key part of the Apple ecosystem, supporting millions of users and billions of transactions. We operate in hundreds of countries and dozens of languages. We strive to provide the best search experience for our customers. If you are passionate about providing the best search results when user ask to play music on iPhone, Apple TV, Apple Watch, HomePod, this is the right place to be! We obsess over search experience on Apple ecosystem and other ecosystems where Apple Music is supported.

Description

As part of our team, you will enhance thousands of compute and big data pipelines to deliver greater scalability, reliability, and efficiency. By leveraging innovative approaches with machine learning and large language models, you will improve pipeline quality, optimize Spark and Kubernetes resource utilization, and create automation that accelerates developer agility.

Responsibilities

• Develop automation and LLM-based agents to automatically increase testing coverage for data pipelines in a monorepo environment.

• Develop automation and LLM-based agents to optimize Spark job resource utilization, including both CPU and memory efficiency.

• Develop LLM-powered agents to automatically diagnose failures in large-scale data pipelines.

• Build tools and automation to accelerate engineer productivity across development, testing, and production deployment of new pipelines.

• Design and maintain dashboards to improve observability of pipeline execution and verification.

• Deliver cost-efficient solutions for storage and compute platform migrations through automation and advanced machine learning techniques.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field.

• 3+ years of experience with large-scale data processing and pipelines.

• Proficiency in Scala, Python, and scripting languages.

• Experience in and solid understanding of distributed systems, performance tuning, and resource optimization.

• Strong hands-on expertise with Apache Spark and the Hadoop ecosystem.

Preferred Qualifications

• Experience developing or applying machine learning techniques or LLM-based agentic workflows for data pipeline optimization and data quality improvements.

• Knowledge of cost optimization strategies for big data infrastructure.

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 $139,500 and $258,100, 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. (https://www.apple.com/careers/us/benefits.html)

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.

Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.