E-3 Visa ML Software Engineer Jobs
ML Software Engineer roles qualify for E-3 visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, machine learning, or a related field. The E-3 has no lottery and no annual cap, so Australian professionals can start the process as soon as they have a job offer.
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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 1,392+ E-3 Visa ML Software Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa ML Software Engineer Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a ML Software Engineer
Translate your Australian degree credentials
U.S. employers and USCIS assess whether your Australian bachelor's degree maps to a U.S. equivalent in a relevant field. A three-year computer science degree from an Australian university is generally accepted, but having a credential evaluation letter ready speeds up the LCA and visa paperwork.
Target companies with active LCA filing history
Search the DOL's Foreign Labor Certification disclosure data to identify employers who have filed LCAs for ML or software engineering roles. Prior filings signal that the hiring team understands the E-3 visa process and won't stall at the sponsorship conversation.
Frame your ML specialization in the job offer letter
The E-3 requires a direct link between your degree and the role. Ask your employer to specify ML-related responsibilities in the offer letter, such as model development, training pipelines, or inference infrastructure, so the specialty occupation requirement is unambiguous in your visa application.
Start the LCA filing before your start date
Your employer must file a certified LCA with the DOL before you can apply for the E-3 at a U.S. consulate in Australia. The DOL targets seven business days for LCA certification, but you should factor this into your timeline when negotiating your start date with the employer.
Use Migrate Mate's E-3 filing service for the full process
Once you have an offer, use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork end-to-end, from DOL submission through consulate appointment preparation. This avoids the coordination gaps that typically delay ML engineering hires when legal responsibility is split between HR and outside counsel.
Clarify E-3 portability before accepting counter-offers
If you receive a competing offer while your E-3 is pending or active, each new employer must file a fresh LCA and you must obtain a new visa stamp for that employer. Negotiate your transition timeline with both parties before making a commitment so your status doesn't lapse between roles.
E-3 Visa ML Software Engineer: Frequently Asked Questions
How do I find ML Software Engineer jobs that offer E-3 visa sponsorship?
Migrate Mate is built specifically for Australian professionals searching for E-3-eligible roles in the U.S. You can filter by job title, location, and sponsorship availability so you're only seeing employers who understand the E-3 process. Most general job search platforms mix visa statuses without filtering for E-3 specifically, which wastes significant time during outreach.
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 Software Engineer role qualify as a specialty occupation for the E-3?
Yes. ML Software Engineer roles consistently meet the specialty occupation standard because they require at minimum a bachelor's degree in computer science, machine learning, mathematics, or a closely related field. USCIS and the DOL assess the degree-to-role connection at the LCA stage, so your offer letter should explicitly describe ML-specific responsibilities rather than generic software development tasks.
How does the E-3 compare to the H-1B for ML Software Engineers?
The E-3 has no lottery and no annual numerical cap, so you can apply any time of year once you have a job offer. The H-1B visa is subject to an oversubscribed annual lottery, meaning most applicants wait years or are never selected. For Australian ML engineers with a qualifying offer, the E-3 provides a direct, predictable path that the H-1B cannot guarantee.
What happens to my E-3 status if I want to change employers in the U.S.?
The E-3 is employer-specific. If you change jobs, your new employer must file a fresh LCA with the DOL and you must obtain a new E-3 visa stamp at a U.S. consulate before starting work, or request a change of status if you're already in the U.S. There is no portability provision like AC21 that applies to the E-3, so plan the transition timeline carefully with both employers.