Electronics Green Card Sponsorship Jobs in Washington
Washington state is one of the strongest markets for electronics Green Card sponsorship in the U.S., driven by major employers like Microsoft, Amazon, Boeing, and a dense cluster of semiconductor and hardware firms around Seattle, Bellevue, and Redmond. Engineers, hardware designers, and embedded systems professionals will find some of the highest concentrations of sponsored roles anywhere in the country.
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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.
Green Card Electronics Job Roles in Washington
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Search Electronics Jobs in WashingtonElectronics Green Card Sponsorship Jobs in Washington: Frequently Asked Questions
Which electronics companies in Washington sponsor Green Cards?
Microsoft, Amazon, Boeing, and Intel (with operations in the Seattle metro) are among the most active Green Card sponsors for electronics roles in Washington. Smaller hardware and semiconductor firms in the Bellevue and Redmond corridors also file regularly. Sponsorship patterns can be verified through USCIS I-140 filing data and DOL PERM disclosure records, which are publicly available.
Which cities in Washington have the most electronics Green Card sponsorship jobs?
Seattle, Bellevue, and Redmond account for the largest share of electronics Green Card sponsorship activity in Washington. Redmond is heavily concentrated around Microsoft's campus, while Seattle hosts Amazon's hardware and devices divisions. Kirkland and Bothell also have notable presences from mid-size electronics and defense electronics firms. Outside the Seattle metro, Everett has aerospace and electronics manufacturing activity tied to Boeing.
What types of electronics roles typically qualify for Green Card sponsorship in Washington?
Roles that most commonly appear in PERM and EB-category filings in the electronics sector include hardware engineers, FPGA engineers, embedded systems engineers, semiconductor process engineers, electrical engineers, and RF engineers. These positions typically require at least a bachelor's degree in electrical engineering, computer engineering, or a closely related field, which supports the specialty occupation standard required for employer-sponsored Green Card petitions.
How do I find electronics Green Card sponsorship jobs in Washington?
Migrate Mate lists electronics jobs in Washington where employers have a documented history of Green Card sponsorship, filtering out roles that don't support international candidates. You can search by role type and filter specifically for Washington state to see active openings in hardware, semiconductor, and embedded systems. Migrate Mate pulls from verified sponsorship data so you're not guessing about which companies will file.
Are there any Washington-specific considerations for electronics Green Card sponsorship?
Washington has no state income tax, which affects total compensation comparisons but does not impact the Green Card process itself. One relevant consideration is that Washington's high concentration of large tech employers means many roles fall under H-1B visa dependent employer rules, which can affect the PERM process and documentation requirements. Electronics professionals in defense-adjacent roles should also be aware that some positions require security clearances that may limit sponsorship eligibility for foreign nationals.
What is the prevailing wage for Green Card 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.