AI ML Engineer Jobs in Seattle, WA
AI ML Engineer jobs in Seattle are in high demand, concentrated in South Lake Union, the Eastside corridor around Bellevue and Redmond, and Capitol Hill's growing tech cluster, across cloud computing, enterprise software, and healthcare AI. Employers hiring right now include Apple, GEICO, and Meta. Scan the live roles below and apply to whichever ones fit.
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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 Seattle
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Who's Hiring
Top Industries Hiring
- Insurance
- Technology & Software
- Electronics & Hardware
- Distribution & Wholesale
- Construction & Real Estate
AI ML Engineer Jobs in Seattle: Frequently Asked Questions
How do I get a ai ml engineer job in Seattle?
Targeting Seattle's dense cloud and enterprise software sector is the most direct route, with companies in South Lake Union and the Eastside corridor consistently posting the most openings. Candidates who demonstrate hands-on experience with large-scale model deployment, MLOps pipelines, or cloud-native infrastructure stand out locally. Contributing to open-source projects, attending Seattle AI and ML meetups, and building a visible portfolio on GitHub all give applicants a concrete edge in this market.
Which companies hire ai ml engineers in Seattle?
Companies currently hiring ai ml engineers in Seattle include Apple, GEICO, and Meta, per current listings on Migrate Mate as of September 2026. Seattle's mix of global tech giants, fast-growing cloud platforms, and well-funded healthcare and biotech startups means openings appear across a wide range of employer sizes and industries.
Are there remote ai ml engineer jobs in Seattle?
Yes, though it varies by specialty since model training and infrastructure roles often require cloud access rather than a fixed office, making them more remote-compatible than hardware or lab-based positions. About 50% of ai ml engineer openings tied to Seattle are remote or hybrid as of September 2026, reflecting broader industry norms. Research science and applied ML roles at Seattle-area companies tend to offer the most flexibility, while on-site presence is more common for roles embedded in product teams.
How can I get a ai ml engineer job in Seattle with little or no experience?
The most realistic entry path in Seattle is targeting associate ML engineer or data scientist roles at mid-size tech companies and AI-focused startups in South Lake Union or the Eastside, where teams are smaller and mentorship is more accessible. Seattle's robust university research ecosystem, including programs at the University of Washington, produces internship and conversion pipelines that entry-level candidates can tap. Building a portfolio with end-to-end ML projects and contributing to open-source frameworks gets attention from local hiring managers who often screen GitHub before a resume.
Which industries hire the most ai ml engineers in Seattle?
The sectors hiring the most ai ml engineers in Seattle are Insurance, Technology & Software, and Electronics & Hardware, based on current listings on Migrate Mate as of September 2026. Seattle's position as a major cloud computing hub, combined with growing investment in healthcare AI and autonomous systems, drives sustained demand for machine learning talent across these industries.
Related Jobs in Washington
See All 17 AI ML Engineer Jobs in Seattle
Find roles in Seattle that match your experience and apply in just a few clicks.
Find AI ML Engineer Jobs