Electronics E-3 Sponsorship Jobs in Washington
Washington state is one of the strongest markets for electronics E-3 visa sponsorship in the U.S., anchored by major employers like Microsoft, Amazon, and Boeing alongside a dense cluster of semiconductor and hardware firms in the Seattle metro and Redmond corridor. Australian engineers and electronics specialists will find consistent demand for specialty occupation roles across the state.
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Get Access To All JobsJoin a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent experiences on Apple products and services. We build robust systems that connect scalable data pipelines with advanced ML workflows, accelerating the development of real-world AI applications. Our work spans the full ML lifecycle, from experimentation to deployment, and you’ll play a key role in shaping how AI models are built, optimized, and scaled. We develop a platform for ML data and features that powers advanced GenAI applications. This includes embeddings (generation, evaluation, ANN search, multimodal support), AI Ops, efficient inference, and a modern feature platform designed to streamline experimentation and drive innovation. We’re looking for engineers and researchers passionate about generative models, data-centric ML, and intelligent systems across diverse real-world use cases. With the autonomy to experiment, the scale to make an impact, and the support to take ideas from prototype to production, you’ll work alongside a world-class team to build intelligent, flexible systems that make ML development faster, more reliable, and more creative.
Description
The Apple Cloud AI Platform team enables Apple's next generation of intelligent products by giving Apple's ML engineers and researchers the data systems and large-scale compute they need to build and ship models at Apple's bar for quality and privacy.
Responsibilities:
As a member of the Apple Cloud AI Platform team, your responsibilities will include:
- Design and build the platform behind Apple's largest model builds - ingestion, immutable versioning, lineage, and governance across structured, unstructured, and multimodal data at petabyte scale, so every model run is reproducible from a versioned dataset
- Develop and evolve Python SDKs and core data libraries that ML engineers depend on to access, transform, and load model-ready datasets across every stage of model development
- Build high-throughput data access and loading primitives that feed Apple's largest GPU fleets, keeping workloads compute-bound rather than I/O-bound
- Build and operate distributed data pipelines spanning Spark, Daft, and Rust-based systems for ingestion, transformation, and large-scale data preparation
- Optimize platform components for tight integration with leading ML frameworks - PyTorch, JAX, and TensorFlow - so dataset access is a first-class concern in the model development loop
- Partner with research and product teams to onboard new data sources, and enable rapid iteration on datasets powering GenAI workloads
- Ensure governance is a first-class platform capability: Legal Terms of Use enforcement, privacy controls, and end-to-end data lineage on every dataset version
- Drive efficiency, reliability, and automation across the data plane and control plane that power Apple's ML fleet
- Continuously evolve platform capabilities to support next-generation workloads, including foundation models, multimodal data, and retrieval-augmented systems
- Diagnose, fix, and automate away complex issues across the stack - from ingestion pipelines to dataset APIs to ML framework integrations - to maximize uptime and throughput
Minimum Qualifications
- Strong foundation in machine learning, with hands-on experience across the end-to-end ML workflow - including data preparation, pipeline development, experimentation, evaluation, and deployment
- Expertise in building and running large scale distributed systems
- Familiarity with modern generative techniques (e.g. transformers, diffusion, retrieval-augmented generation)
- Proven experience building and delivering data and machine learning infrastructure in real-world production environments
- Familiarity with fine-tuning workflows, model optimization, and preparing models for scalable inference
- Familiarity with generative AI and its applications in accelerating and enhancing machine learning workflows
- Experience configuring, deploying and troubleshooting large scale production environments
- Experience in designing, building, and maintaining scalable, highly available systems that prioritize ease of use
- Extensive programming experience in Java, Python or Go
- Strong collaboration and communication (verbal and written) skills
- Comfortable navigating ambiguity and evolving technical landscapes, especially in fast-moving areas
- B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience
Preferred Qualifications
Experience in any of the below is preferred:
- Proficiency with one or more modern ML frameworks (PyTorch, JAX, or TensorFlow), particularly the data loading and dataset access layer
- Columnar and lakehouse formats: Parquet, Iceberg, Delta, or Lance
- Distributed data loading frameworks for ML: Ray Data, NVIDIA DALI, WebDataset, or Mosaic StreamingDataset
- Performance engineering for I/O-bound workloads - Arrow, zero-copy, memory mapping, async I/O
- High-throughput object storage access patterns at GPU scale
- Data lineage and governance systems (DataHub, OpenLineage, Unity Catalog, or equivalent)
- Contributions to or operational experience with Spark, Daft, Polars, or DuckDB internals
- Containerization and orchestration technologies (Docker, Kubernetes)
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 $175,000 and $308,500, 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. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Join a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent experiences on Apple products and services. We build robust systems that connect scalable data pipelines with advanced ML workflows, accelerating the development of real-world AI applications. Our work spans the full ML lifecycle, from experimentation to deployment, and you’ll play a key role in shaping how AI models are built, optimized, and scaled. We develop a platform for ML data and features that powers advanced GenAI applications. This includes embeddings (generation, evaluation, ANN search, multimodal support), AI Ops, efficient inference, and a modern feature platform designed to streamline experimentation and drive innovation. We’re looking for engineers and researchers passionate about generative models, data-centric ML, and intelligent systems across diverse real-world use cases. With the autonomy to experiment, the scale to make an impact, and the support to take ideas from prototype to production, you’ll work alongside a world-class team to build intelligent, flexible systems that make ML development faster, more reliable, and more creative.
Description
The Apple Cloud AI Platform team enables Apple's next generation of intelligent products by giving Apple's ML engineers and researchers the data systems and large-scale compute they need to build and ship models at Apple's bar for quality and privacy.
Responsibilities:
As a member of the Apple Cloud AI Platform team, your responsibilities will include:
- Design and build the platform behind Apple's largest model builds - ingestion, immutable versioning, lineage, and governance across structured, unstructured, and multimodal data at petabyte scale, so every model run is reproducible from a versioned dataset
- Develop and evolve Python SDKs and core data libraries that ML engineers depend on to access, transform, and load model-ready datasets across every stage of model development
- Build high-throughput data access and loading primitives that feed Apple's largest GPU fleets, keeping workloads compute-bound rather than I/O-bound
- Build and operate distributed data pipelines spanning Spark, Daft, and Rust-based systems for ingestion, transformation, and large-scale data preparation
- Optimize platform components for tight integration with leading ML frameworks - PyTorch, JAX, and TensorFlow - so dataset access is a first-class concern in the model development loop
- Partner with research and product teams to onboard new data sources, and enable rapid iteration on datasets powering GenAI workloads
- Ensure governance is a first-class platform capability: Legal Terms of Use enforcement, privacy controls, and end-to-end data lineage on every dataset version
- Drive efficiency, reliability, and automation across the data plane and control plane that power Apple's ML fleet
- Continuously evolve platform capabilities to support next-generation workloads, including foundation models, multimodal data, and retrieval-augmented systems
- Diagnose, fix, and automate away complex issues across the stack - from ingestion pipelines to dataset APIs to ML framework integrations - to maximize uptime and throughput
Minimum Qualifications
- Strong foundation in machine learning, with hands-on experience across the end-to-end ML workflow - including data preparation, pipeline development, experimentation, evaluation, and deployment
- Expertise in building and running large scale distributed systems
- Familiarity with modern generative techniques (e.g. transformers, diffusion, retrieval-augmented generation)
- Proven experience building and delivering data and machine learning infrastructure in real-world production environments
- Familiarity with fine-tuning workflows, model optimization, and preparing models for scalable inference
- Familiarity with generative AI and its applications in accelerating and enhancing machine learning workflows
- Experience configuring, deploying and troubleshooting large scale production environments
- Experience in designing, building, and maintaining scalable, highly available systems that prioritize ease of use
- Extensive programming experience in Java, Python or Go
- Strong collaboration and communication (verbal and written) skills
- Comfortable navigating ambiguity and evolving technical landscapes, especially in fast-moving areas
- B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience
Preferred Qualifications
Experience in any of the below is preferred:
- Proficiency with one or more modern ML frameworks (PyTorch, JAX, or TensorFlow), particularly the data loading and dataset access layer
- Columnar and lakehouse formats: Parquet, Iceberg, Delta, or Lance
- Distributed data loading frameworks for ML: Ray Data, NVIDIA DALI, WebDataset, or Mosaic StreamingDataset
- Performance engineering for I/O-bound workloads - Arrow, zero-copy, memory mapping, async I/O
- High-throughput object storage access patterns at GPU scale
- Data lineage and governance systems (DataHub, OpenLineage, Unity Catalog, or equivalent)
- Contributions to or operational experience with Spark, Daft, Polars, or DuckDB internals
- Containerization and orchestration technologies (Docker, Kubernetes)
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 $175,000 and $308,500, 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. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
E-3 Electronics Job Roles in Washington
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Search Electronics Jobs in WashingtonElectronics E-3 Sponsorship Jobs in Washington: Frequently Asked Questions
Which electronics companies sponsor E-3 visas in Washington?
Microsoft, Amazon, and Boeing are among the largest employers of electronics and hardware professionals in Washington and have established E-3 visa sponsorship track records. Beyond these, companies like Valve, Expedia, and a range of semiconductor and defense electronics firms in the Seattle and Bellevue area regularly sponsor specialty occupation roles. Sponsorship availability varies by team, headcount, and hiring cycle, so confirming directly with the employer matters.
Which cities in Washington have the most electronics E-3 sponsorship jobs?
Seattle and Redmond account for the largest share of electronics E-3 sponsorship activity in Washington, driven by Microsoft's Redmond headquarters and the broader Seattle tech and aerospace ecosystem. Bellevue and Kirkland also have significant hardware and electronics hiring, particularly in consumer electronics and cloud infrastructure. Smaller clusters exist in Everett, where Boeing's manufacturing operations concentrate, and in Bothell, which has a strong medical electronics and defense presence.
What types of electronics roles typically qualify for E-3 sponsorship?
Roles that qualify for E-3 sponsorship must meet the specialty occupation standard, meaning they require a bachelor's degree or higher in a specific technical field. In electronics, this typically includes hardware design engineers, embedded systems engineers, RF and signal processing engineers, PCB design engineers, firmware engineers, and VLSI or semiconductor process engineers. General electronics technician roles that don't require a degree in a specific discipline are less likely to qualify, and the employer must be prepared to demonstrate the degree requirement.
How do I find electronics E-3 sponsorship jobs in Washington?
Migrate Mate is built specifically for this search, letting you filter by visa type, state, and industry to surface electronics E-3 sponsorship roles in Washington without manually screening thousands of listings. Because E-3 eligibility depends on the role meeting specialty occupation requirements and the employer being willing to file, using a platform that pre-filters for sponsorship willingness saves significant time. Migrate Mate's Washington electronics listings pull from employers with documented sponsorship activity.
Are there any Washington-specific considerations for electronics E-3 sponsorship?
Washington has no state income tax, which affects total compensation comparisons but has no bearing on E-3 eligibility or the sponsorship process itself. One practical consideration is that Washington's electronics sector includes significant defense contractors like Boeing and Leidos, and some roles at those employers require security clearances that are not available to E-3 visa holders. Confirming clearance requirements before applying saves time for Australian candidates targeting defense-adjacent electronics positions.
What is the prevailing wage for E-3 electronics jobs in Washington?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.