E-3 Visa Machine Learning Manager Jobs
Machine Learning Manager roles qualify for E-3 visa sponsorship as specialty occupations requiring a bachelor's degree or higher in computer science, data science, or a related field. The E-3 has no lottery and no annual cap, making it a practical path for Australian professionals targeting U.S. ML leadership positions.
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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 211+ E-3 Visa Machine Learning Manager Jobs
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Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a Machine Learning Manager
Frame your degree for specialty occupation
A three-year Australian bachelor's degree is generally accepted as equivalent to a U.S. four-year degree for E-3 visa purposes. Get a credential evaluation from a NACES-member evaluator before your first interview so the document is ready when employers ask.
Target employers with active LCA filing history
Search the DOL's OFLC disclosure data for certified LCAs in computer and information technology occupations. Employers who have filed LCAs before understand the process and are far less likely to withdraw an offer once they see the paperwork involved.
Clarify the manager title in your LCA job duties
LCA job duty descriptions for manager-level ML roles must reflect the specialty occupation requirement. Vague descriptions like 'oversee team' raise DOL scrutiny. Work with your employer to specify model development oversight, research direction, and degree-level technical requirements.
Use Migrate Mate's E-3 filing service for your LCA
The LCA must be certified by DOL before your consulate appointment. Use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork end-to-end, so nothing delays your start date after an offer is signed.
Address dual intent directly at the consulate
Consular officers assess nonimmigrant intent for E-3 applicants. If you're on a manager track that could lead to a green card, prepare a clear explanation of your current nonimmigrant intent. The E-3 doesn't prohibit immigrant intent by statute, but a clear narrative reduces the risk of a 221(g) administrative hold.
Time your job search around LCA processing
DOL targets LCA certification within seven business days, but delays happen. Build at least three weeks between signing your offer and your planned consulate appointment. Negotiating a start date without accounting for LCA processing is one of the most common causes of delayed E-3 approvals.
E-3 Visa Machine Learning Manager: Frequently Asked Questions
How do I find Machine Learning Manager jobs with E-3 visa sponsorship?
Migrate Mate is built specifically for Australian professionals searching for E-3 sponsorship roles in the U.S. Filter by job title and visa type to surface Machine Learning Manager positions at employers who already understand the E-3 process. This saves significant time compared to manually screening employers who have no E-3 filing history.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does a Machine Learning Manager role qualify as a specialty occupation for the E-3?
Yes, provided the role requires a bachelor's degree or higher in a specific technical field such as computer science, data science, or machine learning. Generic manager titles can raise questions during the LCA stage, so the job description must clearly articulate the degree-level technical requirements, not just team leadership responsibilities.
How does the E-3 compare to the H-1B for Machine Learning Manager roles?
The E-3 has no annual lottery and no numerical cap, so you can apply at any time of year without being excluded by chance. The H-1B visa has an 85,000-slot annual cap with a lottery that turns away most applicants. For Australian professionals, the E-3 is a direct and repeatable path that doesn't depend on random selection.
Can I change employers while on an E-3 as a Machine Learning Manager?
Yes, but you need to restart the process with the new employer. The new employer files a fresh LCA with DOL and you attend a new consulate appointment, or file a change of status with USCIS if you're already in the U.S. You can begin working for the new employer once the new E-3 is approved, not before.