E-3 Visa AI ML Engineer Jobs
AI ML Engineer roles qualify for E-3 visa sponsorship as specialty occupations requiring a bachelor's degree in computer science, data science, or a related field. The E-3 has no lottery and no annual cap, so you can apply any time you have a qualifying offer from a U.S. employer.
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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 1,527+ E-3 Visa AI ML Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa AI ML Engineer Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as an AI ML Engineer
Align your degree to the role
U.S. consular officers assess whether your degree field matches the job. A computer science or data science degree maps cleanly to AI ML Engineer roles, but a general IT or engineering degree may require supporting documentation showing relevant coursework or specialization.
Target employers with LCA filing history
Search the DOL's Office of Foreign Labor Certification disclosure data to identify companies that have previously filed Labor Condition Applications for ML or data science roles. These employers already understand the E-3 visa process and are less likely to stall on sponsorship.
Clarify sponsorship early in interviews
Many U.S. tech hiring managers confuse the E-3 with the H-1B lottery. During interviews, explain that the E-3 requires no lottery, has a 10,500 annual allocation that has never been exhausted, and takes weeks, not months, to obtain.
Get your transcript evaluated before applying
Australian three-year bachelor's degrees are generally accepted for E-3 specialty occupation purposes, but having a credential evaluation ready before you apply removes a common employer objection and speeds up the LCA filing stage.
Use Migrate Mate's E-3 filing service for the paperwork
Once you have an offer, Migrate Mate's E-3 filing service handles the LCA submission to DOL, visa application preparation, and consulate appointment readiness, so your employer doesn't need to engage a separate immigration attorney.
Time your application around consulate availability
E-3 visas are issued at Australian consulates in Sydney, Melbourne, and Perth. Appointment wait times vary by location and season. Confirm your preferred consulate's current availability before accepting a start date with your employer.
E-3 Visa AI ML Engineer: Frequently Asked Questions
How do I find AI ML Engineer jobs that offer E-3 visa sponsorship?
Use Migrate Mate to search AI ML Engineer roles filtered by E-3 visa sponsorship. Most general job boards don't distinguish between visa types, so you can spend hours applying to roles where sponsorship isn't available. Migrate Mate surfaces employers who have demonstrated willingness to sponsor E-3 applicants, saving you time at the targeting stage.
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 an AI ML Engineer role qualify as a specialty occupation for the E-3?
Yes. AI ML Engineer roles require at least a bachelor's degree in computer science, data science, mathematics, or a closely related field, which meets the DOL and USCIS specialty occupation standard. The key is that your degree field must align with the specific role. A general business or unrelated engineering degree may not be sufficient without supporting documentation showing relevant technical coursework.
How does the E-3 compare to the H-1B for AI ML Engineer roles?
For Australian nationals, the E-3 is significantly more practical than the H-1B. The H-1B has an annual cap of 85,000 with a heavily oversubscribed lottery, meaning you could wait years before getting selected. The E-3 has a 10,500 annual cap that has never been fully used, no lottery, and can be applied for at any time of year once you have a qualifying job offer.
Can I switch AI ML Engineer employers on an E-3 visa?
Yes, but each employer change requires a new E-3 process. Your new employer must file a fresh Labor Condition Application with the DOL, and you'll need to either apply for a new E-3 visa at an Australian consulate or, in some cases, change status from within the U.S. There's no portability provision like some other visa categories, so plan your transition timeline carefully.