Electronics H-1B Sponsorship Jobs in Washington
Washington is one of the most active states for electronics H-1B visa sponsorship, anchored by major employers like Microsoft, Amazon, Boeing, and Paccar in the greater Seattle-Bellevue corridor. Hardware engineering, semiconductor design, and embedded systems roles are well represented across Redmond, Kirkland, and the broader Puget Sound region, making Washington a strong target for electronics professionals seeking H-1B sponsorship.
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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.
H-1B Electronics Job Roles in Washington
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Search Electronics Jobs in WashingtonElectronics H-1B Sponsorship Jobs in Washington: Frequently Asked Questions
Which electronics companies sponsor H-1B visas in Washington?
Washington has a strong base of H-1B visa sponsors in electronics. Microsoft and Amazon are among the highest-volume H-1B filers in the state, with significant hardware and embedded systems teams in Redmond and Seattle. Boeing sponsors H-1B workers in avionics and electrical engineering roles near Everett and Renton. Smaller hardware-focused companies in Bellevue and Kirkland also appear regularly in DOL Labor Condition Application filings for electronics positions.
Which cities in Washington have the most electronics H-1B sponsorship jobs?
Seattle and Bellevue account for the largest share of electronics H-1B sponsorship activity in Washington. Redmond is notable specifically for hardware and device engineering due to Microsoft's campus presence. Everett and Renton see demand in aerospace electronics through Boeing. Kirkland has a growing concentration of hardware startups. Most opportunities are concentrated in the I-405 and I-5 corridors along the greater Puget Sound region.
What types of electronics roles typically qualify for H-1B sponsorship?
H-1B sponsorship in electronics generally applies to specialty occupations requiring at least a bachelor's degree in a directly related field. In Washington, commonly sponsored roles include hardware engineers, electrical engineers, embedded systems engineers, FPGA designers, RF engineers, and PCB design engineers. The key requirement is that the position must normally require a specific technical degree, not just any bachelor's degree, to meet USCIS specialty occupation standards.
How do I find electronics H-1B sponsorship jobs in Washington?
Migrate Mate is built specifically for international job seekers and filters electronics H-1B sponsorship jobs in Washington by visa type, industry, and location. Because sponsorship willingness is not always stated in standard job postings, using a platform like Migrate Mate that surfaces employers with a documented H-1B filing history in electronics saves significant time. You can filter directly for Washington-based roles in the Electronics and Hardware category.
Are there any state-specific considerations for H-1B sponsorship in Washington's electronics sector?
Washington has no state income tax, which affects compensation structures employers may present, though H-1B prevailing wage requirements are determined federally by DOL wage data for each role and location regardless. Washington's electronics sector is concentrated enough that some specialized roles, particularly in aerospace electronics or consumer hardware, may have fewer active sponsors than software engineering positions, making employer research through LCA disclosure data a useful step before applying.
What is the prevailing wage for H-1B 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.