E-3 Visa ML Engineer Jobs
ML Engineer roles in the U.S. qualify as E-3 visa specialty occupations, meaning Australian nationals can secure visa sponsorship without entering a lottery. The E-3 renews indefinitely in two-year increments, so a single employer willing to file an LCA can support a long-term U.S. career in machine learning.
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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 1,532+ E-3 Visa ML Engineer Jobs
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Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a ML Engineer
Frame your degree field precisely
Computer science, statistics, and electrical engineering degrees map cleanly to ML Engineer roles under E-3 specialty occupation rules. A general IT or business degree may require a detailed equivalency argument, so gather transcripts and course descriptions before any employer conversation.
Target employers with existing LCA filings
Search the DOL's OFLC disclosure data for companies that have filed LCAs under ML or software engineering job titles. These employers already understand the process and are far less likely to withdraw an offer once they see E-3 sponsorship is required.
Use Migrate Mate to find sponsors fast
Migrate Mate filters U.S. ML Engineer roles by E-3 visa sponsorship availability, so you're not cold-applying to employers who've never heard of the visa. Use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork once an offer lands.
Clarify remote work status before signing
Your LCA lists a specific worksite address. If your ML role is fully remote or split across multiple offices, the employer must file separate LCA certifications for each location. Confirm this with your hiring manager before you accept an offer.
Prepare a specialty occupation memo proactively
Consular officers occasionally question whether an ML Engineer role meets the degree-required standard, particularly at startups without HR infrastructure. Ask your employer to prepare a brief job duties memo referencing DOL's Occupational Employment and Wage Statistics data for the SOC code.
Time your consulate appointment around LCA certification
The LCA must be DOL-certified before you can lodge a visa application. DOL targets seven business days for standard certification. Build that window into your start-date negotiation so your employer isn't pressuring a consulate appointment before the paperwork is ready.
E-3 Visa ML Engineer: Frequently Asked Questions
How do I find ML Engineer jobs that offer E-3 visa sponsorship?
Migrate Mate is the most direct way to search for ML Engineer roles filtered specifically by E-3 sponsorship availability. Most general job boards don't distinguish between visa types, so you end up applying to roles where the employer has never filed an LCA. Migrate Mate surfaces companies already set up to sponsor Australian nationals under the E-3.
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 ML Engineer role qualify as a specialty occupation for the E-3?
Yes. ML Engineer positions consistently require at least a bachelor's degree in computer science, mathematics, statistics, or a closely related engineering field, which satisfies the E-3 specialty occupation definition. Roles that list a degree as preferred rather than required can create problems, so review the job description carefully before your employer files the LCA.
How does the E-3 compare to the H-1B for ML Engineers?
The E-3 has no lottery and no annual cap, so your employer can file any time of year and expect a decision without random selection. H-1B visa registration opens once a year in March, with roughly a one-in-four chance of selection. For Australian ML Engineers, the E-3 is a direct path that doesn't depend on lottery luck or a specific filing window.
Can I switch ML Engineer employers after arriving on an E-3?
Yes, but each new employer must file a fresh LCA and you need a new E-3 visa stamp if you leave the U.S. before starting the new role. If you're already in the U.S., you can begin working for the new employer once the LCA is certified and the new visa documentation is in order, without waiting for a new consulate appointment in most cases.