Sr. Applied AI/ML Engineer, Rights and Pricing - Apple Services Engineering
Apple
Software Engineering, Data Science
Cupertino, CA, USA
USD 212k-318,400 / year + Equity
Posted on Jan 21, 2026
The Apple Services Engineering team is one of the most exciting examples of Apple’s long-held passion for combining art and technology. These are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And they do it on a massive scale, meeting Apple’s high expectations with high performance to deliver a huge variety of entertainment in over 37 languages to more than 175 countries. These engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services. Thanks to Apple’s unique integration of hardware, software, and services, engineers here partner to get behind a single unified vision. That vision always includes a deep dedication to strengthening Apple’s privacy policy, one of Apple’s core values. Although services are a bigger part of Apple’s business than ever before, these teams remain small, nimble, and cross-functional, offering greater exposure to the array of opportunities here.
The Rights & Pricing engineering team provides the Apple Services platform for distribution rights by country, calculation and management of prices including retail, offers, wholesale, and tax. Rights & Pricing also includes Partner Onboarding which includes the vendor application process, signing of digital contracts, collection of bank account and tax information, and business systems that manage the presentation layers of payments, invoicing, and financial reporting. This is a key team for Apple Services Engineering! As a Senior Applied AI/ML Engineer, you will shape how our team adopts AI/ML—from rapid prototyping to production systems at scale. You'll identify high-impact opportunities, build proof-of-concepts to validate ideas, then leverage Apple's internal ML infrastructure to productionize solutions serving millions of users. Beyond building, you'll establish best practices, mentor engineers to become AI-native practitioners, and help define our AI/ML culture for years to come. Sound like a great opportunity? Join us!
- Lead AI/ML initiatives end-to-end—from prototyping and experimentation to production deployment
- Develop and fine-tune models (including LLMs) for rights management, pricing optimization, and partner operations
- Create compelling demos that communicate AI capabilities and inform product direction
- Build reusable patterns and documentation that enable engineers to incorporate AI/ML into their work
- Partner with product and business teams to identify automation opportunities
- Establish evaluation frameworks and standards for responsible AI development
- Mentor engineers and influence AI/ML adoption across the team
- BS/MS/PhD in a quantitative field (Computer Science, Math, Statistics, Physics, etc.) and 5+ years of industry experience
- Proven track record of leading successful AI/ML projects from conception to deployment
- BS/MS/PhD in a quantitative field (Computer Science, Math, Statistics, Physics, etc.) and 5+ years of applied AI/ML experience
- Demonstrated experience solving business problems with the help of AI/ML, developing reliable evaluation frameworks to assess model efficiency, and scaling operations to large-scale production deployments
- Strong proficiency with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience with ML pipelines (feature engineering, training, serving, monitoring)
- Proficiency in Python and experience with distributed systems
- Proven ability to mentor and influence engineering teams on AI/ML adoption and leading mission-critical initiatives
- Excellent communication skills with ability to translate technical concepts for diverse audiences
- Hands-on experience with LLMs, including: developing evaluation frameworks, fine-tuning, prompt engineering, RAG architectures, and AI API integration
- Experience establishing AI/ML practices in teams new to AI/ML
- Background in optimization, pricing algorithms, or financial systems
- Experience with privacy-preserving ML techniques
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