Machine Learning Manager Jobs at Apple with Visa Sponsorship
Machine Learning Manager jobs at Apple sit at the intersection of research leadership and product scale, overseeing teams that ship ML capabilities across hardware, software, and services. Apple sponsors multiple visa categories for this function, making it a realistic target for international candidates with strong technical leadership backgrounds.
Find Machine Learning Manager Jobs at AppleOverview
Showing 5 of 17+ Machine Learning Manager Jobs at Apple
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all Machine Learning Manager Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Manager Jobs at Apple.
Get Access To All JobsINTRODUCTION
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 make Apple Intelligence possible.
We value strong software engineering fundamentals combined with a 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
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
PREFERRED QUALIFICATIONS
- BS, MS, or PhD in Computer Science, Machine Learning, or related field (or equivalent industry experience)
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.
INTRODUCTION
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 make Apple Intelligence possible.
We value strong software engineering fundamentals combined with a 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
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
PREFERRED QUALIFICATIONS
- BS, MS, or PhD in Computer Science, Machine Learning, or related field (or equivalent industry experience)
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.
See all Machine Learning Manager Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Manager Jobs at Apple.
Get Access To All JobsTips for Finding Machine Learning Manager Jobs at Apple
Align your portfolio with Apple's ML stack
Apple's ML work spans on-device inference, neural engine optimization, and privacy-preserving models. Frame your experience around deployment constraints and hardware-software co-design, not just model accuracy metrics, so your background maps directly to what hiring managers evaluate.
Target roles requiring cross-functional team leadership
Apple structures ML Manager roles around owning both research direction and engineering execution across product groups. Highlight experience managing mixed teams of researchers and engineers shipping to production, which differentiates you from pure research or pure engineering management candidates.
Prepare your credentials for specialty occupation documentation
For H-1B sponsorship, USCIS requires evidence that the role is a specialty occupation. Gather transcripts, any advanced degree certifications, and documentation of progressively specialized ML work early, before the offer stage, so Apple's immigration counsel can move quickly.
Time your application around H-1B cap and OPT windows
If you're on F-1 OPT, Apple can file an H-1B cap-subject petition in April for an October 1 start. Confirm your OPT expiration date before accepting an offer so your employer's counsel has enough runway to bridge any gap with a cap-gap extension.
Use Migrate Mate to filter verified Apple ML sponsorship openings
Apple posts Machine Learning Manager roles across multiple business units and career sites. Use Migrate Mate to filter active Apple roles that align with your target visa type, so you're applying to positions where sponsorship is already confirmed rather than assumed.
Ask explicitly about PERM timing if you want a Green Card path
For EB-2 or EB-3 sponsorship, Apple's immigration team initiates the DOL PERM labor certification process. Ask during offer negotiation whether Apple starts PERM within the first year of employment, since the earlier you file, the earlier your priority date is established.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Machine Learning Managers?
Yes, Apple sponsors H-1B visas for Machine Learning Manager roles. The H-1B is the most common work visa path for this position given the degree requirements and specialized nature of the work. Apple also sponsors the H-1B1 visa for Singaporean and Chilean nationals, and the E-3 visa for Australian citizens, offering alternatives that bypass the H-1B lottery entirely.
How do I apply for Machine Learning Manager jobs at Apple?
Apply directly through Apple's careers site or use Migrate Mate to browse verified Machine Learning Manager openings at Apple filtered by your visa type. Apple's hiring process for this level typically includes a recruiter screen, technical assessments on ML system design and leadership scenarios, and several rounds of cross-functional interviews before an offer is extended.
Which visa types does Apple commonly use for Machine Learning Manager roles?
Apple sponsors H-1B, H-1B1 visa, E-3, and TN visas for nonimmigrant work authorization in this role. For permanent residency, Apple files EB-2 and EB-3 petitions through the DOL PERM labor certification process. F-1 OPT and CPT are also supported, giving candidates already in the U.S. on student status a bridge while H-1B sponsorship is initiated.
What qualifications does Apple expect for a Machine Learning Manager?
Apple typically expects a graduate degree in machine learning, computer science, or a related field, combined with demonstrated experience managing ML teams that have shipped products at scale. Hands-on technical depth is weighted heavily alongside leadership credentials. Experience with on-device ML, privacy-preserving techniques, or Apple's Neural Engine is a distinguishing factor at the manager level.
How do I handle the timing between an Apple offer and my visa filing?
Once Apple extends an offer, their immigration counsel files the Labor Condition Application with the DOL before submitting the H-1B petition to USCIS. The full process from offer to approved status can take three to six months without premium processing. If you're transferring from another employer, Apple can file an H-1B transfer petition and you can start on a receipt notice under portability rules.