E-3 Visa Senior ML Engineer Jobs
Senior ML Engineer roles in the U.S. qualify as E-3 specialty occupations, requiring a bachelor's degree in computer science, machine learning, or a related field. Australian citizens can secure E-3 visa sponsorship without entering a lottery, making these roles far more accessible than comparable H-1B visa positions.
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Get Access To All JobsINTRODUCTION
The Apple Ray team is seeking a Senior / Staff Software Engineer with strong distributed systems expertise and a solid background in machine learning. In this hybrid role, you will design and build core components of Apple’s unified data+ML platform powered by open-source Ray, while also partnering with ML teams to ensure the platform meets the needs of large-scale training and inference workloads.
You will contribute to the distributed runtime, orchestration layer, and system APIs that power Apple’s intelligent features across products and services. This role is ideal for a software engineer who enjoys low-level systems work but is also fluent in ML workflows and models at scale.
Description
Apple Ray integrates deeply with Apple’s data and ML ecosystem to provide a unified platform for building, orchestrating, and scaling complex ML and data pipelines. As a Software Engineer with ML background, you will design distributed systems that support large-scale model training, tuning, and inference across heterogeneous compute environments—from bare-metal GPU clusters to cloud-native infrastructure.
You will build features that enhance developer productivity for ML engineers, improve resource efficiency, and advance the performance and reliability of Apple’s ML workloads. You’ll collaborate closely with ML practitioners to translate model and pipeline needs into robust platform capabilities, while also improving the underlying distributed runtime and control plane.
This role requires strong engineering fundamentals, hands-on experience with ML systems, and a passion for building scalable infrastructure.
Responsibilities
-
Build scalable distributed systems and platform components using Ray that power Apple’s data+ML workflows.
-
Develop APIs, libraries, and services that improve the efficiency and usability of large-scale ML training and inference pipelines.
-
Optimize performance and resource utilization across GPU/CPU clusters for ML workloads running at Apple scale.
-
Collaborate with ML teams to understand model and pipeline needs and translate them into robust platform features.
-
Design fault-tolerant orchestration mechanisms, autoscaling strategies, and runtime improvements for distributed ML jobs.
-
Diagnose complex issues across distributed systems and ML pipelines to ensure reliability and availability.
-
Improve observability, monitoring, and debugging capabilities targeted at ML-centric distributed workloads.
-
Contribute to architectural decisions and, where appropriate, upstream enhancements to Ray and related tools.
MINIMUM QUALIFICATIONS
-
6+ years building distributed systems, high-scale backend services, or compute runtimes.
-
Solid background in ML workflows, model training, model serving, or data pipeline development.
-
Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java).
-
Experience with ML frameworks such as PyTorch or TensorFlow and familiarity with GPU-based training.
-
Understanding of parallelism strategies, model scaling, or distributed training concepts.
-
Experience with cluster orchestration (Kubernetes, EKS, GKE) or large-scale compute systems.
-
Strong debugging skills across distributed and ML-centric runtime environments.
-
Ability to work cross-functionally with ML engineers, data engineers, and infrastructure teams.
-
B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or related technical fields - or comparable software engineering experience.
PREFERRED QUALIFICATIONS
-
Experience with distributed training frameworks (DeepSpeed, Horovod, FSDP, ZeRO).
-
Background in optimizing GPU workloads or performance benchmarking.
-
Experience with model orchestration systems or ML platforms.
-
Contributions to open-source ML or distributed systems projects.
-
Familiarity with large-scale data systems such as Spark, Flink, or similar.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
INTRODUCTION
The Apple Ray team is seeking a Senior / Staff Software Engineer with strong distributed systems expertise and a solid background in machine learning. In this hybrid role, you will design and build core components of Apple’s unified data+ML platform powered by open-source Ray, while also partnering with ML teams to ensure the platform meets the needs of large-scale training and inference workloads.
You will contribute to the distributed runtime, orchestration layer, and system APIs that power Apple’s intelligent features across products and services. This role is ideal for a software engineer who enjoys low-level systems work but is also fluent in ML workflows and models at scale.
Description
Apple Ray integrates deeply with Apple’s data and ML ecosystem to provide a unified platform for building, orchestrating, and scaling complex ML and data pipelines. As a Software Engineer with ML background, you will design distributed systems that support large-scale model training, tuning, and inference across heterogeneous compute environments—from bare-metal GPU clusters to cloud-native infrastructure.
You will build features that enhance developer productivity for ML engineers, improve resource efficiency, and advance the performance and reliability of Apple’s ML workloads. You’ll collaborate closely with ML practitioners to translate model and pipeline needs into robust platform capabilities, while also improving the underlying distributed runtime and control plane.
This role requires strong engineering fundamentals, hands-on experience with ML systems, and a passion for building scalable infrastructure.
Responsibilities
-
Build scalable distributed systems and platform components using Ray that power Apple’s data+ML workflows.
-
Develop APIs, libraries, and services that improve the efficiency and usability of large-scale ML training and inference pipelines.
-
Optimize performance and resource utilization across GPU/CPU clusters for ML workloads running at Apple scale.
-
Collaborate with ML teams to understand model and pipeline needs and translate them into robust platform features.
-
Design fault-tolerant orchestration mechanisms, autoscaling strategies, and runtime improvements for distributed ML jobs.
-
Diagnose complex issues across distributed systems and ML pipelines to ensure reliability and availability.
-
Improve observability, monitoring, and debugging capabilities targeted at ML-centric distributed workloads.
-
Contribute to architectural decisions and, where appropriate, upstream enhancements to Ray and related tools.
MINIMUM QUALIFICATIONS
-
6+ years building distributed systems, high-scale backend services, or compute runtimes.
-
Solid background in ML workflows, model training, model serving, or data pipeline development.
-
Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java).
-
Experience with ML frameworks such as PyTorch or TensorFlow and familiarity with GPU-based training.
-
Understanding of parallelism strategies, model scaling, or distributed training concepts.
-
Experience with cluster orchestration (Kubernetes, EKS, GKE) or large-scale compute systems.
-
Strong debugging skills across distributed and ML-centric runtime environments.
-
Ability to work cross-functionally with ML engineers, data engineers, and infrastructure teams.
-
B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or related technical fields - or comparable software engineering experience.
PREFERRED QUALIFICATIONS
-
Experience with distributed training frameworks (DeepSpeed, Horovod, FSDP, ZeRO).
-
Background in optimizing GPU workloads or performance benchmarking.
-
Experience with model orchestration systems or ML platforms.
-
Contributions to open-source ML or distributed systems projects.
-
Familiarity with large-scale data systems such as Spark, Flink, or similar.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See all 685+ E-3 Visa Senior ML Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa Senior ML Engineer Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a Senior ML Engineer
Frame your ML credentials for U.S. specialty occupation
Your Australian three-year bachelor's degree is generally accepted as equivalent to a U.S. four-year degree, but document the equivalency explicitly. Include transcripts, course outlines, and any postgraduate work so your employer's LCA filing stands on firm ground.
Target employers with active DOL LCA filing history
Search the DOL's Office of Foreign Labor Certification disclosure data for companies that have filed LCAs for machine learning or software engineering roles. Prior LCA activity signals the hiring team already understands E-3 visa sponsorship requirements and won't stall on your offer.
Clarify the E-3 timeline before accepting an offer
The LCA certification typically takes seven business days, followed by a consulate appointment. Ask your prospective employer when they expect to file so you can align your start date, especially if you're transitioning from another visa status.
Use Migrate Mate's E-3 filing service for end-to-end filing
Once you have an offer, use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork. The service manages everything from DOL prevailing wage certification through to your consulate appointment, reducing the risk of documentation errors that can delay your start date.
Distinguish ML Engineer from data scientist in job documents
USCIS and DOL evaluate specialty occupation based on the role as described, not the employer's internal title. Ensure your offer letter, LCA, and support letter consistently describe ML engineering duties tied to a specific degree field, not a generalist data role.
Address E-3 dual intent limitations early in negotiations
The E-3 is a nonimmigrant visa that doesn't permit dual intent, so if you plan to pursue permanent residency later, raise that with your employer before filing. Sponsors who understand this dynamic can structure a longer-term immigration plan alongside your initial E-3.
E-3 Visa Senior ML Engineer: Frequently Asked Questions
How do I find Senior ML Engineer jobs that offer E-3 visa sponsorship?
Migrate Mate is built specifically for this search. It surfaces Senior ML Engineer roles where employers have demonstrated E-3 or equivalent sponsorship willingness, so you're not cold-applying to companies unfamiliar with the visa. Filtering by role and visa type gets you to relevant opportunities without manually cross-referencing DOL disclosure databases.
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 Senior ML Engineer role qualify as an E-3 specialty occupation?
Yes. Senior ML Engineer positions require at minimum a bachelor's degree in computer science, electrical engineering, mathematics, or a closely related field, which satisfies the E-3 specialty occupation standard. The key is that the role's duties must theoretically and practically require that specific degree. Generalist engineering titles that accept any bachelor's degree can create LCA complications, so your offer letter should describe ML-specific responsibilities.
How does the E-3 visa compare to H-1B for Senior ML Engineers?
The E-3 has a 10,500 annual cap that has never been fully used, so there's no lottery and no random selection. H-1B requires registration in an annual lottery with far lower odds of selection. For Australian ML engineers, this means you can receive and accept an offer and begin the filing process immediately, without waiting for a lottery result in April or deferring a start date by up to a year.
Can I transfer my E-3 if I change ML engineering roles or employers?
Yes, but each new employer must file a fresh LCA with the DOL and you'll need to attend a new consulate appointment or, if you're already in the U.S., your employer can file a change of status petition. There's no portability mechanism like AC21 that exists for H-1B holders, so plan for a processing gap of several weeks between roles.