Sr Machine Learning Manager, Intelligent System Experience

The Apple Intelligence Platform team builds the foundational on-device software infrastructure that powers Apple Intelligence. We develop the APIs, platforms, and systems that enable breakthrough features like Writing Tools, Siri, Visual Intelligence, and Image Playground. Our work spans the full software stack - from low-level inference engines and runtime optimization to high-level platform APIs like the Foundation Models API.

Our mission is to build production-ready software platforms that deliver magical experiences to millions of users. We work closely with research teams to understand new ML techniques, then focus on the engineering challenges of building robust, scalable systems to ship them. Whether it's designing APIs for agentic workflows, optimizing inference pipelines, implementing efficient caching strategies for attention mechanisms, or creating infrastructure for search and retrieval, we're focused on the platform engineering and software architectures that makes Apple Intelligence possible.

We value strong software engineering fundamentals combined with deep understanding of ML systems and techniques. Our team members know how to build production platforms that are reliable, performant, and maintainable at scale, while also understanding the ML primitives - transformers, attention, KV caches, kernels - that power these systems. We're looking for a leader who can drive platform development, build strong engineering teams, and deliver the software infrastructure that powers Apple Intelligence features used by millions every day.

Description

As a Senior Machine Learning Manager on the Apple Intelligence Platform team, you will lead a team of engineers building critical platform infrastructure and APIs that power features used by millions of Apple customers daily. You'll be responsible for the technical execution and delivery of software systems that span the platform stack - from runtime engines and inference pipelines to developer-facing APIs and service integrations. This role requires someone who deeply understands both ML fundamentals and platform engineering, able to make informed architectural decisions about how to build software systems that efficiently support modern ML techniques.

You will work cross-functionally with researchers, product teams, and platform engineers to build the production software systems needed to ship new capabilities. Success in this role means delivering robust, well-architected platforms that leverage your understanding of ML to enable world-class Apple Intelligence experiences.

Responsibilities:

Lead and grow a team of platform engineers building ML infrastructure, APIs, and services for Apple Intelligence

Build production software platforms to support new ML techniques, translating research innovations into shippable, scalable systems

Ensure platforms meet Apple's standards for performance, reliability, scalability, privacy, and user experience

Make large-scale architectural decisions

Guide development of APIs and frameworks for agentic workflows and complex multi-step ML systems

Establish engineering excellence through software architecture standards, code quality practices, testing, and operational rigor

Mentor engineers on platform engineering, ML systems implementation, API design, and production software best practices

Partner with product and engineering leaders to align platform capabilities with feature requirements and business goals

Preferred Qualifications

BS, MS, or PhD in Computer Science, Machine Learning, or related field (or equivalent industry experience)

Minimum Qualifications

8+ years of experience in ML platform engineering, ML infrastructure, or related fields, with 3+ years in technical leadership or management roles

Deep understanding of ML fundamentals including neural network architectures, transformers, attention mechanisms, and inference optimization

Strong software engineering fundamentals with expertise in systems design, API architecture, and distributed systems

Proven experience building and shipping production ML APIs, platforms, or infrastructure at scale

Strong knowledge of ML software stacks and modeling primitives: KV caching, kernel methods, attention architectures, and efficient inference techniques

Hands-on experience with ML frameworks (PyTorch, TensorFlow, JAX), serving systems, and production ML deployment

Understanding of modern agentic workflows, multi-step reasoning systems, and API design for complex ML applications

Track record of leading engineering teams and delivering complex ML platform projects from conception to production

Strong architectural skills with experience making technical decisions for large-scale, high-performance ML systems

Excellent communication and collaboration skills with ability to work across research, product, and engineering teams

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 $262,500 and $433,400, 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.