E-3 Visa Machine Learning Research Jobs
Machine Learning Research roles qualify as E-3 specialty occupations, making Australian professionals eligible for U.S. employer sponsorship without entering a lottery. The E-3 visa is renewable indefinitely in two-year increments, so you can build a long-term research career at U.S. labs, universities, and tech companies without the H-1B visa cap pressure.
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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 1,401+ E-3 Visa Machine Learning Research Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa Machine Learning Research Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship in Machine Learning Research
Frame your research credentials for U.S. employers
Australian PhD and honours degrees translate directly to U.S. specialty occupation standards, but your CV needs to show publication records, conference presentations, and model deployment experience in terms U.S. hiring committees recognise.
Target employers with active DOL LCA filings
Search the DOL's Office of Foreign Labor Certification disclosure data for companies that have filed LCAs for ML research titles. This confirms an employer already understands the E-3 visa process and has sponsored similar roles before.
Clarify the specialty occupation case before accepting an offer
Not every ML title passes the specialty occupation test. Roles framed as general data analysis or software engineering may not qualify. Confirm the job description explicitly requires a degree in computer science, statistics, or a directly related field before you sign.
Use Migrate Mate's E-3 filing service for LCA and consulate prep
Once you have an offer, use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork end-to-end. The LCA must be DOL-certified before your consulate appointment, and timing errors here are the most common cause of delays.
Find ML Research jobs on Migrate Mate
Migrate Mate filters job listings by E-3 sponsorship availability, so you're only seeing employers already set up to hire Australians. Search by ML Research job title to surface active roles without wading through listings that will reject your visa status.
Negotiate your start date around E-3 consulate wait times
Sydney, Melbourne, and Perth consulates have different appointment availability. Build at least four to six weeks between your signed offer and your proposed start date so your employer's LCA certification and your consulate slot align without forcing a rushed rescheduling.
E-3 Visa Machine Learning Research: Frequently Asked Questions
How do I find Machine Learning Research jobs that offer E-3 visa sponsorship?
Migrate Mate is built specifically for this search. It surfaces Machine Learning Research roles from employers already willing to sponsor Australian nationals on an E-3 visa, so you're not filtering out irrelevant listings manually. Because the E-3 has no lottery and relatively low employer cost compared to H-1B, more research-focused employers are open to it than you might expect.
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 Research role qualify as a specialty occupation for E-3 purposes?
Most ML Research positions do qualify, provided the job description requires a bachelor's degree or higher in a specific field such as computer science, machine learning, statistics, or applied mathematics. Roles that only list a degree as preferred rather than required, or that accept any field of study, can fail the specialty occupation test. Review the job description carefully before applying.
How does the E-3 visa compare to H-1B for Machine Learning Research roles?
The E-3 has a 10,500 annual cap that has never been reached, so there's no lottery and no random selection risk. H-1B requires entering an annual lottery where selection is not guaranteed. For ML Research roles, both visas require the employer to file an LCA with DOL and demonstrate prevailing wage compliance, but the E-3 timeline is significantly more predictable.
Can I switch ML Research employers while on an E-3 visa?
Yes, but each new employer must file a fresh LCA with the DOL and you'll need a new E-3 visa stamp before re-entering the U.S. if you travel internationally. If you remain inside the U.S. and your current E-3 status is still valid, you can begin work for a new employer while their LCA is pending, though specific timing rules apply.