AI ML Intern Jobs in Washington
AI ML Intern jobs in Washington concentrate in the technology, cloud computing, and aerospace sectors, with Seattle, Bellevue, and Redmond standing as the most active hiring metros in the state. Microsoft, Amazon, and Boeing maintain deep AI and machine learning programs in Washington, regularly bringing on interns across natural language processing, computer vision, and applied ML research. Washington is among the most active markets in the country for early-career AI talent, with openings at every level from undergraduate to graduate-stage candidates. See the openings below and apply to the ones that match your experience.
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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 9 AI ML Intern Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI ML Intern JobsAI ML Intern Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
AI ML Intern Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Distribution & Wholesale
What Washington Employers Look For
The qualifications that appear most often in AI ML intern jobs across Washington.
- Enrollment in a bachelor's or master's degree program in computer science, data science, or a related field
- Hands-on experience with Python and at least one machine learning framework such as TensorFlow or PyTorch
- Familiarity with data preprocessing, model training, and evaluation methodologies
- Experience with cloud platforms such as Azure, AWS, or Google Cloud is strongly preferred by Washington employers
- Strong mathematical foundation in linear algebra, probability, and statistics
- Demonstrated project work, GitHub portfolio, or research contributions in an AI or ML domain
AI ML Intern Jobs in Washington: Frequently Asked Questions
How do you become a ai ml intern in Washington?
AI ML intern roles in Washington do not require a state-issued license or credential. The standard path is enrollment in a computer science, data science, or related degree program at a Washington university such as the University of Washington or Washington State University, combined with coursework in machine learning and a demonstrable project portfolio. Internship applications typically open in the fall for the following summer, and candidates who complete relevant coursework and build public project repositories are most competitive.
Which companies hire ai ml interns in Washington?
Washington ai ml intern roles are posted by Meta, Google, and Oracle and others right now, based on current listings on Migrate Mate as of September 2026. Washington's concentration of major technology headquarters and research labs means intern programs here are among the largest and most structured in the country.
Which Washington cities have the most ai ml intern jobs?
Seattle and Olympia are the Washington cities with the most ai ml intern openings. Seattle and Bellevue anchor the distribution because Microsoft, Amazon, and a dense network of AI startups and research labs are headquartered there, while Redmond's role as Microsoft's global campus makes it a consistent source of structured intern programs throughout the year.
Are there remote ai ml intern jobs in Washington?
Yes, and more than most fields. About 0% of ai ml intern openings tied to Washington are remote or hybrid as of September 2026, reflecting the desk-based and analytical nature of most machine learning work. Research-focused and software-heavy intern roles tend to be the most remote-friendly, while positions involving proprietary hardware, lab infrastructure, or in-person team collaboration are more likely to require on-site presence.
How can I get hired as a ai ml intern in Washington with little or no experience?
The most realistic entry path is applying to formal intern programs at large Washington technology employers, which are designed for candidates who are still building experience. Microsoft's Explore and intern programs and Amazon's university hiring pipelines both accept candidates without prior professional ML experience, prioritizing coursework and project portfolios instead. Contributing to open-source machine learning projects, completing Kaggle competitions, and publishing code publicly on GitHub are the credentials that give Washington candidates the clearest edge when formal experience is limited.
Where can I find and apply to ai ml intern jobs in Washington?
You can find and apply to ai ml intern jobs in Washington on Migrate Mate, which lists current Washington openings. Search the listings to find roles that match your background, skills, and preferred location, then apply directly to the ones that fit.
See All 9 AI ML Intern Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI ML Intern Jobs