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 On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting-edge machine learning models that power magical user experiences on Apple's hardware and software platforms.
The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations.
This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.
Our group is seeking an Engineering Manager to lead the Performance Tools and Services team, with a focus on the tools, services, and infrastructure that make on-device ML performance measurable, understandable, and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them, and the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.
DESCRIPTION
We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis.
This role focuses on giving ML developers fast, accurate, and actionable insight into how their models execute on Apple devices. We're looking for a manager that has proven experience in and passion for providing high quality developer tools and capabilities in the fast paced and dynamic space of ML.
As the manager in this role, you will lead a diverse team spanning full-stack web development, backend services, distributed systems, and low-level on-device performance tooling. You will partner with leaders across the organization and company to develop our platform while supporting clients internally and externally.
The role requires a solid technical understanding of ML execution on device, performance analysis and profiling, and the systems that connect low-level signals to framework-level (e.g., PyTorch) semantics.
Responsibilities
-
Leading and growing the team that builds the frontend web services for introspecting ML models and their on-device execution, the backend services that support them, and the on-device toolchain for gathering and reporting low-level performance data.
-
Driving future efforts to improve the “model authoring performance profiling improve model repeat“ workflow, making it faster and more insightful for ML developers.
-
Owning the infrastructure for running ML inference across fleets of devices, ensuring it is reliable, scalable, and produces trustworthy performance data.
-
Attracting, hiring, and guiding the career of talented ML, software, and tools engineers.
-
Working with cross functional partners to push the state-of-the-art of on-device ML functionality and performance.
MINIMUM QUALIFICATIONS
-
BS/MS/PhD in Computer Science or Electrical Engineering.
-
Two or more years of strong and validated management experience.
-
Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch).
-
Experience delivering web services and/or developer-facing tools, spanning frontend and backend.
-
Excellent communication skills.
-
Track record of creating clean software architectures, intuitive designs, and high-performance extensible software.
-
Solid programming skills in at least one of the following languages: Python, Swift, Objective-C, C/C++.
PREFERRED QUALIFICATIONS
-
Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch).
-
Experience with performance profiling, benchmarking, and analysis tooling.
-
Experience building and operating infrastructure for running workloads across fleets of devices.
-
Experience associating low-level performance data with framework-level operations.
-
Experience with MLIR / LLVM compiler technologies.
PAY & BENEFITS
This posting is not for a specific job opening and by submitting your resume you are expressing interest in being contacted about this type of role at Apple in the future.
INTRODUCTION
The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting-edge machine learning models that power magical user experiences on Apple's hardware and software platforms.
The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations.
This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.
Our group is seeking an Engineering Manager to lead the Performance Tools and Services team, with a focus on the tools, services, and infrastructure that make on-device ML performance measurable, understandable, and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them, and the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.
DESCRIPTION
We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis.
This role focuses on giving ML developers fast, accurate, and actionable insight into how their models execute on Apple devices. We're looking for a manager that has proven experience in and passion for providing high quality developer tools and capabilities in the fast paced and dynamic space of ML.
As the manager in this role, you will lead a diverse team spanning full-stack web development, backend services, distributed systems, and low-level on-device performance tooling. You will partner with leaders across the organization and company to develop our platform while supporting clients internally and externally.
The role requires a solid technical understanding of ML execution on device, performance analysis and profiling, and the systems that connect low-level signals to framework-level (e.g., PyTorch) semantics.
Responsibilities
-
Leading and growing the team that builds the frontend web services for introspecting ML models and their on-device execution, the backend services that support them, and the on-device toolchain for gathering and reporting low-level performance data.
-
Driving future efforts to improve the “model authoring performance profiling improve model repeat“ workflow, making it faster and more insightful for ML developers.
-
Owning the infrastructure for running ML inference across fleets of devices, ensuring it is reliable, scalable, and produces trustworthy performance data.
-
Attracting, hiring, and guiding the career of talented ML, software, and tools engineers.
-
Working with cross functional partners to push the state-of-the-art of on-device ML functionality and performance.
MINIMUM QUALIFICATIONS
-
BS/MS/PhD in Computer Science or Electrical Engineering.
-
Two or more years of strong and validated management experience.
-
Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch).
-
Experience delivering web services and/or developer-facing tools, spanning frontend and backend.
-
Excellent communication skills.
-
Track record of creating clean software architectures, intuitive designs, and high-performance extensible software.
-
Solid programming skills in at least one of the following languages: Python, Swift, Objective-C, C/C++.
PREFERRED QUALIFICATIONS
-
Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch).
-
Experience with performance profiling, benchmarking, and analysis tooling.
-
Experience building and operating infrastructure for running workloads across fleets of devices.
-
Experience associating low-level performance data with framework-level operations.
-
Experience with MLIR / LLVM compiler technologies.
PAY & BENEFITS
This posting is not for a specific job opening and by submitting your resume you are expressing interest in being contacted about this type of role at Apple in the future.
See all 1,533+ E-3 Visa Machine Learning Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa Machine Learning Manager Jobs.
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.