Machine Learning Engineer Visa Sponsorship Jobs in Washington
Washington is one of the strongest states for machine learning engineer visa sponsorship, driven by Microsoft, Amazon, and Google's major presence in the Seattle metro area. Bellevue, Redmond, and Seattle collectively host some of the largest ML engineering teams in the country, with Puget Sound's tech corridor offering consistent sponsorship activity across cloud, search, and AI infrastructure roles.
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Get Access To All JobsAbout the Role
Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
What You Will Do
- Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
- Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
- Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
Basic Qualifications
- Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
- 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)
Preferred Qualifications
- Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others
- Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
- Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
- Proficiency in reinforcement learning and causal machine learning
Compensation
For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Ready to Ride?
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
About the Role
Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
What You Will Do
- Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
- Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
- Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
Basic Qualifications
- Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
- 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)
Preferred Qualifications
- Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others
- Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
- Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
- Proficiency in reinforcement learning and causal machine learning
Compensation
For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Ready to Ride?
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Machine Learning Engineer Job Roles in Washington
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Search Machine Learning Engineer Jobs in WashingtonMachine Learning Engineer Jobs in Washington: Frequently Asked Questions
Which companies sponsor visas for machine learning engineers in Washington?
Microsoft in Redmond, Amazon in Seattle, and Google in Kirkland are among the most active sponsors for machine learning engineers in Washington. Apple, Meta, and Expedia also maintain significant ML teams in the greater Seattle area. Beyond the largest employers, a number of mid-size AI and cloud infrastructure companies in the Puget Sound region have established sponsorship track records for specialized ML roles.
Which visa types are most common for machine learning engineer roles in Washington?
The H-1B visa is the most common visa for machine learning engineers in Washington, as the role consistently qualifies as a specialty occupation requiring a relevant bachelor's degree or higher in computer science, statistics, or a related field. Candidates with an approved I-140 may also work under H-1B extensions beyond the six-year cap. Australians may qualify for the E-3 visa, and Canadians and Mexicans may qualify under TN visa status in applicable engineering categories.
Which cities in Washington have the most machine learning engineer sponsorship jobs?
Seattle and Redmond account for the largest share of machine learning engineer sponsorship jobs in Washington. Bellevue and Kirkland also see strong demand, particularly from Amazon's and Google's satellite offices. Smaller but growing activity exists in Bothell and Issaquah, where biotech and defense technology companies have begun expanding their applied ML teams. Most open sponsored roles are concentrated within the Seattle metropolitan area.
How to find machine learning engineer visa sponsorship jobs in Washington?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it easier to identify machine learning engineer roles in Washington without sifting through postings from employers who do not sponsor. You can search by state and role type to surface positions from companies actively hiring internationally. Migrate Mate focuses exclusively on sponsored roles, which saves significant time compared to scanning general job boards where sponsorship status is rarely stated upfront.
Are there state-specific factors that affect machine learning engineer sponsorship in Washington?
Washington has no state income tax, which affects prevailing wage comparisons since federal wage benchmarks are set against local cost-of-living data for the Seattle-Bellevue-Tacoma metro area. The University of Washington in Seattle produces a large pipeline of ML talent that major employers are already set up to sponsor. Washington's concentration of large tech employers also means many companies have established in-house immigration teams, which can simplify and accelerate the sponsorship process compared to employers doing it for the first time.
What is the prevailing wage for sponsored machine learning engineer 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.