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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Get Access To All JobsINTRODUCTION TO THE TEAM
The Multi-Product AI team at Expedia Group enables unforgettable travel experiences. The team’s responsibilities cover search ranking & recommendations for Brand Expedia across core lines of business including Flights, Cars, Packages, and Activities. Additionally, we’re responsible for optimizing our interactions with travelers across this domain, including cache optimization, price forecasting, and next-best action modeling. Our approaches include both traditional ML as well as GenAI-based solutions. We work closely with other teams in the Data & AI organization to continually improve our tools, processes, and platforms for building and deploying industry leading AI solutions. The Machine Learning Scientist II will own complex projects within our team’s scope. You will utilize a variety of techniques to solve challenging business problems and act as a full-stack contributor to delivering AI solutions. You will work with a dynamic group of product managers, engineers, and scientists to achieve Expedia’s business goals.
ROLE AND RESPONSIBILITIES
In this role, you will:
- Design and implement end-to-end model pipelines to production across multiple product domains, including ranking, recommendations, search, and personalization
- Develop and maintain scalable data pipelines, data quality checks, and model monitoring to ensure reliability, performance, and responsible behavior of ML systems in production
- Collaborate with cross-functional partners (product, analytics, engineering) to translate ambiguous business needs into well-scoped ML projects, communicate findings, and influence decision making with data-driven insights
- Use A/B tests and offline/online evaluation frameworks to measure model impact and guide iterative improvement
MINIMUM QUALIFICATIONS
- Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience
- 2+ years of relevant professional experience
- Professional industry experience applying machine learning or statistical modeling to real business problems, including end-to-end model development from data exploration through evaluation and deployment
- Proficiency in Python and with ML frameworks and libraries for model development, training, and evaluation
- Demonstrated ability to translate problem statements into well-defined ML tasks, design appropriate model and data structures (including APIs and data models), and own solutions within a defined product, service, or feature area, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products with attention to safety and reliability
PREFERRED QUALIFICATIONS
- Graduate degree in a quantitative field (such as Computer Science, Statistics, Machine Learning, Operations Research, or similar) with focused coursework or research in ML, optimization, or statistical modeling
- Experience with modern ranking & recommendation modeling approaches in an applied, production setting
- Track record of optimizing ML systems in production, including monitoring, alerting, retraining, and model governance to ensure performance, robustness, and fairness
- Experience designing and improving ML architectures at scale, including model selection, feature store design, and API/data model choices that support low-latency, high-availability production systems
- Familiarity with natural language search techniques and agentic workflows
LOCATION
Please note that this role is only available in the following locations: Austin and Seattle in alignment with our flexible work model which requires employees to be in-office at least three days a week. We are unable to offer relocation assistance for this role.
INTRODUCTION TO THE TEAM
The Multi-Product AI team at Expedia Group enables unforgettable travel experiences. The team’s responsibilities cover search ranking & recommendations for Brand Expedia across core lines of business including Flights, Cars, Packages, and Activities. Additionally, we’re responsible for optimizing our interactions with travelers across this domain, including cache optimization, price forecasting, and next-best action modeling. Our approaches include both traditional ML as well as GenAI-based solutions. We work closely with other teams in the Data & AI organization to continually improve our tools, processes, and platforms for building and deploying industry leading AI solutions. The Machine Learning Scientist II will own complex projects within our team’s scope. You will utilize a variety of techniques to solve challenging business problems and act as a full-stack contributor to delivering AI solutions. You will work with a dynamic group of product managers, engineers, and scientists to achieve Expedia’s business goals.
ROLE AND RESPONSIBILITIES
In this role, you will:
- Design and implement end-to-end model pipelines to production across multiple product domains, including ranking, recommendations, search, and personalization
- Develop and maintain scalable data pipelines, data quality checks, and model monitoring to ensure reliability, performance, and responsible behavior of ML systems in production
- Collaborate with cross-functional partners (product, analytics, engineering) to translate ambiguous business needs into well-scoped ML projects, communicate findings, and influence decision making with data-driven insights
- Use A/B tests and offline/online evaluation frameworks to measure model impact and guide iterative improvement
MINIMUM QUALIFICATIONS
- Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience
- 2+ years of relevant professional experience
- Professional industry experience applying machine learning or statistical modeling to real business problems, including end-to-end model development from data exploration through evaluation and deployment
- Proficiency in Python and with ML frameworks and libraries for model development, training, and evaluation
- Demonstrated ability to translate problem statements into well-defined ML tasks, design appropriate model and data structures (including APIs and data models), and own solutions within a defined product, service, or feature area, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products with attention to safety and reliability
PREFERRED QUALIFICATIONS
- Graduate degree in a quantitative field (such as Computer Science, Statistics, Machine Learning, Operations Research, or similar) with focused coursework or research in ML, optimization, or statistical modeling
- Experience with modern ranking & recommendation modeling approaches in an applied, production setting
- Track record of optimizing ML systems in production, including monitoring, alerting, retraining, and model governance to ensure performance, robustness, and fairness
- Experience designing and improving ML architectures at scale, including model selection, feature store design, and API/data model choices that support low-latency, high-availability production systems
- Familiarity with natural language search techniques and agentic workflows
LOCATION
Please note that this role is only available in the following locations: Austin and Seattle in alignment with our flexible work model which requires employees to be in-office at least three days a week. We are unable to offer relocation assistance for this role.
Machine Learning Scientist Job Roles 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 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.
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