Machine Learning Scientist Visa Sponsorship Jobs in Washington
Washington is one of the most active states for machine learning scientist visa sponsorship, driven by major tech employers in the Seattle metro including Microsoft, Amazon, Apple, and Google. Bellevue and Redmond anchor the hiring corridor, with additional demand from cloud infrastructure, autonomous systems, and biotech research teams across the region.
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Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.
AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This position is for a Software Engineer that will lead the development of machine learning tools to run, optimize, and analyze machine learning workloads. This candidate must have had experience leading machine learning tool projects, preferably starting from architecture through several generations of delivery to customers. Deep knowledge of profiling and optimization, resource management, scheduling, code generation are needed. The ideal candidate will have worked on new instruction set architectures, which may include CPU, NPU, GPU and other forms of compute.
Key job responsibilities
This engineer will lead the design and implementation of ML infrastructure platform, building systems for capacity management, workload scheduling, and fleet orchestration across ML accelerators. They will work with ML scientists, training infrastructure engineers, hardware teams, and internal customers to ensure the ML Infra service delivers seamless ML Accelerator access with low wait times, high utilization, and zero-config deployment from various environments.
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:
- Build high-impact solutions to deliver to our large customer base.
- Participate in design discussions, code review, and communicate with internal and external stakeholders.
- Work cross-functionally to help drive business decisions with your technical input.
- Work in a startup-like development environment, where you’re always working on the most important stuff.
About the team
- High-impact, high-visibility: You'll directly accelerate every Neuron team's ability to ship — your work multiplies the output of 100+ engineers
- Greenfield opportunities: We're actively building new capabilities with significant design ownership for SDEs
- Small, senior team: where every person owns major components and drives architectural decisions
- AI infrastructure: Work at the intersection of Kubernetes, custom silicon, and large-scale ML workloads
Diverse Experiences
We value diverse experiences and non-traditional career paths. If your career is just starting or includes alternative experiences, we encourage you to apply.
Inclusive Team Culture
Our employee-led affinity groups foster inclusion. Events like CORE and AmazeCon inspire us to embrace our uniqueness.
Work/Life Balance
We strive for flexibility as part of our working culture, supporting you both at work and at home.
Mentorship & Career Growth
We offer knowledge-sharing, mentorship, and one-on-one code reviews to help you grow as a professional.
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience designing, building, operating, and managing large-scale distributed systems or web services
- 2+ years of experience designing and developing large-scale, multi-tiered, multi-threaded, distributed software applications, tools, systems, and services in Go, Java, or Rust
- Experience in computer science fundamentals, including object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
PREFERRED QUALIFICATIONS
- Experience in debugging, profiling, and implementing software engineering best practices in large-scale systems
- Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- 5+ years of server-side development experience
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience leading and influencing your team or organization
- Experience building and operating large-scale distributed systems, including on Kubernetes/EKS
- Strong proficiency in Java or Rust and Python, and working knowledge of JavaScript/TypeScript
- Experience in an operational role owning production services, including on-call rotation, incident response, root cause analysis, and driving fixes for availability and latency
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
DESCRIPTION
Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.
AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This position is for a Software Engineer that will lead the development of machine learning tools to run, optimize, and analyze machine learning workloads. This candidate must have had experience leading machine learning tool projects, preferably starting from architecture through several generations of delivery to customers. Deep knowledge of profiling and optimization, resource management, scheduling, code generation are needed. The ideal candidate will have worked on new instruction set architectures, which may include CPU, NPU, GPU and other forms of compute.
Key job responsibilities
This engineer will lead the design and implementation of ML infrastructure platform, building systems for capacity management, workload scheduling, and fleet orchestration across ML accelerators. They will work with ML scientists, training infrastructure engineers, hardware teams, and internal customers to ensure the ML Infra service delivers seamless ML Accelerator access with low wait times, high utilization, and zero-config deployment from various environments.
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:
- Build high-impact solutions to deliver to our large customer base.
- Participate in design discussions, code review, and communicate with internal and external stakeholders.
- Work cross-functionally to help drive business decisions with your technical input.
- Work in a startup-like development environment, where you’re always working on the most important stuff.
About the team
- High-impact, high-visibility: You'll directly accelerate every Neuron team's ability to ship — your work multiplies the output of 100+ engineers
- Greenfield opportunities: We're actively building new capabilities with significant design ownership for SDEs
- Small, senior team: where every person owns major components and drives architectural decisions
- AI infrastructure: Work at the intersection of Kubernetes, custom silicon, and large-scale ML workloads
Diverse Experiences
We value diverse experiences and non-traditional career paths. If your career is just starting or includes alternative experiences, we encourage you to apply.
Inclusive Team Culture
Our employee-led affinity groups foster inclusion. Events like CORE and AmazeCon inspire us to embrace our uniqueness.
Work/Life Balance
We strive for flexibility as part of our working culture, supporting you both at work and at home.
Mentorship & Career Growth
We offer knowledge-sharing, mentorship, and one-on-one code reviews to help you grow as a professional.
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience designing, building, operating, and managing large-scale distributed systems or web services
- 2+ years of experience designing and developing large-scale, multi-tiered, multi-threaded, distributed software applications, tools, systems, and services in Go, Java, or Rust
- Experience in computer science fundamentals, including object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
PREFERRED QUALIFICATIONS
- Experience in debugging, profiling, and implementing software engineering best practices in large-scale systems
- Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- 5+ years of server-side development experience
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience leading and influencing your team or organization
- Experience building and operating large-scale distributed systems, including on Kubernetes/EKS
- Strong proficiency in Java or Rust and Python, and working knowledge of JavaScript/TypeScript
- Experience in an operational role owning production services, including on-call rotation, incident response, root cause analysis, and driving fixes for availability and latency
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
Machine Learning Scientist Job Roles in Washington
See all 309+ Machine Learning Scientist Jobs in Washington
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Search Machine Learning Scientist Jobs in WashingtonMachine Learning Scientist Jobs in Washington: Frequently Asked Questions
Which companies sponsor visas for machine learning scientists in Washington?
Microsoft, Amazon, Google, Apple, and Meta have consistent histories of sponsoring work visas for machine learning scientists in Washington, particularly through their Seattle and Redmond campuses. Beyond the major tech firms, companies like Zillow, Expedia, T-Mobile, and a growing number of AI-focused startups in the Seattle area also sponsor qualified candidates for these roles regularly.
Which visa types are most common for machine learning scientist roles in Washington?
The H-1B visa is the most common visa category for machine learning scientists in Washington, as the role typically requires a master's or doctoral degree in computer science, statistics, or a closely related field, satisfying the specialty occupation requirement. Candidates with advanced degrees from U.S. universities may be eligible for the H-1B cap exemption under the master's cap. The O-1A is an alternative for candidates with demonstrated exceptional ability, such as published research or significant industry recognition.
Which cities in Washington have the most machine learning scientist sponsorship jobs?
Seattle and Redmond account for the large majority of machine learning scientist sponsorship activity in Washington. Microsoft's Redmond headquarters and Amazon's Seattle campus are among the highest-volume H-1B filers nationally for this role type. Bellevue has grown significantly as a secondary hub, with several large tech employers maintaining engineering offices there. Kirkland also has meaningful presence, particularly through Google's local engineering campus.
How to find machine learning scientist visa sponsorship jobs in Washington?
Migrate Mate is built specifically for international candidates seeking visa sponsorship roles, and filters directly for machine learning scientist positions in Washington. Because sponsorship willingness is not always stated in standard job postings, using a platform that surfaces verified sponsoring employers saves significant time. Migrate Mate aggregates active openings from companies with documented sponsorship histories, so you can focus your applications on roles where sponsorship is a realistic possibility.
Are there any Washington-specific factors that affect machine learning scientist sponsorship?
Washington has no state income tax, which affects prevailing wage calculations under Department of Labor methodology since compensation structures here often include equity heavily weighted against base salary. University of Washington is a significant pipeline for machine learning talent, and its OPT and STEM OPT graduates frequently enter sponsorship processes with Seattle-area employers. Washington's concentration of large tech employers also means more cap-exempt H-1B filings through institutions affiliated with nonprofits or universities, though this is role and employer dependent.
What is the prevailing wage for sponsored machine learning scientist 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.