AI ML Engineer Jobs in Washington
AI ML Engineer jobs in Washington are among the most active in the country, with strong demand from entry-level data scientists through principal engineers concentrated in cloud computing, enterprise software, autonomous systems, and aerospace AI. Seattle, Bellevue, and Redmond anchor the market, where Microsoft, Amazon, and Boeing maintain deep and ongoing hiring for machine learning infrastructure, computer vision, and large language model development. Natural language processing, MLOps, and reinforcement learning are the sub-areas drawing the most consistent job postings. Find a role that fits below and apply directly.
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- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Seattle, WA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience with image processing, computer vision, or machine learning applications.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of this team, you will focus on productionizing GenAI shopping features across Google’s most prominent surfaces, including Search, Commerce, Ads, Chrome, and YouTube. Here, you will master the art of scaling multimodal GenAI to production-level quality, leveraging Google’s infrastructure to deliver highly customized, industry-defining user experiences.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Seattle, WA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience with image processing, computer vision, or machine learning applications.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of this team, you will focus on productionizing GenAI shopping features across Google’s most prominent surfaces, including Search, Commerce, Ads, Chrome, and YouTube. Here, you will master the art of scaling multimodal GenAI to production-level quality, leveraging Google’s infrastructure to deliver highly customized, industry-defining user experiences.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
See All 17 AI ML Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI ML Engineer JobsAI ML Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
AI ML Engineer Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Insurance
- Technology & Software
- Electronics & Hardware
- Distribution & Wholesale
- Construction & Real Estate
What Washington Employers Look For
The qualifications that appear most often in AI ML engineer jobs across Washington.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch
- Hands-on experience designing, training, and deploying machine learning models at scale
- Familiarity with cloud ML platforms, particularly AWS SageMaker or Azure Machine Learning
- Experience with MLOps practices including model versioning, monitoring, and CI/CD pipelines
- Strong foundation in statistics, linear algebra, and algorithmic problem-solving
AI ML Engineer Jobs in Washington: Frequently Asked Questions
How do you become a ai ml engineer in Washington?
Washington has no state-issued license for ai ml engineers, so the path runs through education and demonstrated technical skill. Most Washington employers look for a bachelor's or master's degree in computer science, mathematics, or a related field, followed by hands-on project work or research experience. Graduates from the University of Washington, Washington State University, or local coding and data science programs who build a portfolio of deployed models are competitive for entry and mid-level roles.
Which companies hire ai ml engineers in Washington?
Employers hiring ai ml engineers in Washington right now include Apple, GEICO, and Meta, based on current listings on Migrate Mate as of September 2026. Washington's concentration of major tech headquarters and cloud infrastructure operations means openings frequently involve production-scale systems rather than purely research-focused work.
Which Washington cities have the most ai ml engineer jobs?
Seattle and Olympia are the Washington cities with the most ai ml engineer openings. Seattle and Bellevue lead because Microsoft, Amazon, and a dense cluster of AI-focused startups and scale-ups are headquartered there, while Redmond draws volume specifically from Microsoft's campus and its partner ecosystem in the surrounding corridor.
Are there remote ai ml engineer jobs in Washington?
Yes, and more than most fields. About 50% of ai ml engineer openings tied to Washington are remote or hybrid as of September 2026, reflecting how well the role's core work, including model development, experimentation, and code review, translates to distributed teams. Roles that require on-site GPU clusters or close collaboration with hardware teams are more likely to be in-person.
How can I get hired as a ai ml engineer in Washington with little or no experience?
The most realistic entry path is a machine learning or data science internship, since Microsoft, Amazon, and Boeing all run structured internship and new-graduate programs that convert to full-time offers. Lateral moves from data analyst, software development engineer, or research assistant roles are common stepping stones. Building a public GitHub portfolio with end-to-end ML projects and earning a cloud certification such as AWS Machine Learning Specialty or the Microsoft Azure AI Engineer credential gives candidates a measurable edge when competing against more experienced applicants.
Where can I find and apply to ai ml engineer jobs in Washington?
You can find and apply to ai ml engineer jobs in Washington on Migrate Mate, which lists current Washington openings updated regularly. Search the listings, find roles that match your background and target companies, and apply directly to the positions that fit.
See All 17 AI ML Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI ML Engineer Jobs