AI ML Platform Jobs in Washington
AI ML Platform jobs in Washington rank among the most active markets in the country, concentrated in cloud infrastructure, enterprise software, and research-driven technology sectors, with openings at every level from associate ML engineer through principal platform architect. Seattle, Redmond, and Bellevue account for the largest share of hiring, anchored by employers such as Microsoft, Amazon, and Google, all of which maintain major Washington engineering campuses. The most in-demand specialties are MLOps pipeline development, model serving infrastructure, and distributed training systems. Find a role that fits below and apply directly.
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In this role, you will own the strategy and roadmap for foundational platforms across Data, ML, and Measurement, enabling teams to rapidly build, experiment, and productionize machine learning solutions. Your mission is to enable ML builders to move from idea to production faster by removing bottlenecks across the ML lifecycle, from data ingestion and feature engineering to model training, deployment, and experimentation, so teams can iterate faster while providing robust measurement capabilities that shorten iteration cycles and consistently improve customer experiences.
You will operate in highly complex domains including recommendation systems, real-time inference, large-scale distributed training, LLM infrastructure, and partner closely with engineering and science leaders to influence architecture, drive adoption, and deliver measurable business outcomes.
Key job responsibilities
- Define and drive the multi-year vision and roadmap for ML platform and infrastructure supporting personalization, discovery, content intelligence, and emerging GenAI experiences
- Develop and own the data platform strategy, delivering clean, curated datasets that encode business logic and provide science teams with trusted, model-ready data foundations
- Build end-to-end ML tooling and pipelines that enable ML builders to discover datasets, ideate modeling approaches, conduct research and experimentation, and seamlessly productionize models from prototype to production
- Support large-scale model training, real-time inference, and compute optimization across CPU and GPU to ensure models perform efficiently at production scale
- Define and evolve the feature store strategy, supporting both online and offline data serving while minimizing online/offline skew to ensure consistency between training and serving environments
- Own the developer experience for ML builders by delivering self-service tools, reusable components, and standardized workflows that increase productivity, reduce operational overhead, and improve cost efficiency, scalability, and availability
- Enhance the measurement platform to monitor model performance in production, track input and output metric alignment, and ensure models deliver intended business outcomes
- Influence senior leadership and cross-functional stakeholders to align on platform strategy, investment priorities, and trade-offs
- Drive adoption of platform capabilities across teams by ensuring solutions are intuitive, reliable, and measurably better than existing workflows
About the team
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.
As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.
We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!
BASIC QUALIFICATIONS
- 7+ years of end to end product delivery experience
- 4+ years of technical product or program management experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience leading engineering discussions around technology decisions and strategy related to a product
- 3+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Deep understanding of MLOps, model training, evaluation metrics and data pipelines.
PREFERRED QUALIFICATIONS
- Experience in project management methodologies, business analysis, or process improvement
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
- Familiarity with recommendation systems is a bonus
- Fluency in technology alternatives with ability to weigh pros and cons of different technical approaches
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 197,900.00 - 267,800.00 USD annually
USA, WA, SEATTLE - 179,900.00 - 243,400.00 USD annually
DESCRIPTION
In this role, you will own the strategy and roadmap for foundational platforms across Data, ML, and Measurement, enabling teams to rapidly build, experiment, and productionize machine learning solutions. Your mission is to enable ML builders to move from idea to production faster by removing bottlenecks across the ML lifecycle, from data ingestion and feature engineering to model training, deployment, and experimentation, so teams can iterate faster while providing robust measurement capabilities that shorten iteration cycles and consistently improve customer experiences.
You will operate in highly complex domains including recommendation systems, real-time inference, large-scale distributed training, LLM infrastructure, and partner closely with engineering and science leaders to influence architecture, drive adoption, and deliver measurable business outcomes.
Key job responsibilities
- Define and drive the multi-year vision and roadmap for ML platform and infrastructure supporting personalization, discovery, content intelligence, and emerging GenAI experiences
- Develop and own the data platform strategy, delivering clean, curated datasets that encode business logic and provide science teams with trusted, model-ready data foundations
- Build end-to-end ML tooling and pipelines that enable ML builders to discover datasets, ideate modeling approaches, conduct research and experimentation, and seamlessly productionize models from prototype to production
- Support large-scale model training, real-time inference, and compute optimization across CPU and GPU to ensure models perform efficiently at production scale
- Define and evolve the feature store strategy, supporting both online and offline data serving while minimizing online/offline skew to ensure consistency between training and serving environments
- Own the developer experience for ML builders by delivering self-service tools, reusable components, and standardized workflows that increase productivity, reduce operational overhead, and improve cost efficiency, scalability, and availability
- Enhance the measurement platform to monitor model performance in production, track input and output metric alignment, and ensure models deliver intended business outcomes
- Influence senior leadership and cross-functional stakeholders to align on platform strategy, investment priorities, and trade-offs
- Drive adoption of platform capabilities across teams by ensuring solutions are intuitive, reliable, and measurably better than existing workflows
About the team
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.
As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.
We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!
BASIC QUALIFICATIONS
- 7+ years of end to end product delivery experience
- 4+ years of technical product or program management experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience leading engineering discussions around technology decisions and strategy related to a product
- 3+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Deep understanding of MLOps, model training, evaluation metrics and data pipelines.
PREFERRED QUALIFICATIONS
- Experience in project management methodologies, business analysis, or process improvement
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
- Familiarity with recommendation systems is a bonus
- Fluency in technology alternatives with ability to weigh pros and cons of different technical approaches
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 197,900.00 - 267,800.00 USD annually
USA, WA, SEATTLE - 179,900.00 - 243,400.00 USD annually
See All 5 AI ML Platform Jobs in Washington
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Find AI ML Platform JobsAI ML Platform Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
AI ML Platform 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
- Retail
- Construction & Real Estate
What Washington Employers Look For
The qualifications that appear most often in AI ML platform jobs across Washington.
- Bachelor's or master's degree in computer science, machine learning, or a related engineering field
- Hands-on experience building or maintaining ML training and inference pipelines at scale
- Proficiency with Python and at least one ML framework such as PyTorch or TensorFlow
- Familiarity with cloud-native infrastructure on AWS, Azure, or Google Cloud Platform
- Experience with containerization and orchestration tools including Docker and Kubernetes
- Strong understanding of MLOps practices including model versioning, monitoring, and deployment automation
AI ML Platform Jobs in Washington: Frequently Asked Questions
How do you become a ai ml platform in Washington?
Most Washington employers require a bachelor's degree in computer science, software engineering, or a directly related field, with a master's degree preferred for platform-focused roles. There is no state-issued license for this role in Washington. The practical path involves building hands-on experience with ML infrastructure tools, contributing to open-source MLOps projects, and earning cloud certifications from providers like AWS or Google Cloud, which Washington hiring managers treat as meaningful signals of platform competency.
Which companies hire ai ml platforms in Washington?
Employers hiring ai ml platforms in Washington right now include Apple, GEICO, and Amazon, based on current listings on Migrate Mate as of September 2026. Washington's concentration of major cloud and enterprise technology headquarters means platform engineering roles here often involve production systems operating at significant scale.
Which Washington cities have the most ai ml platform jobs?
Seattle are the Washington cities with the most ai ml platform openings. Seattle and Redmond together drive the majority of demand, powered by the dense cluster of cloud and enterprise software campuses there, while Bellevue has grown as a secondary hub as several large technology employers have expanded their East Side offices and engineering footprints in recent years.
How can I get hired as a ai ml platform in Washington with little or no experience?
The most realistic entry point is an associate or junior ML engineer role that involves platform tooling rather than pure research, which several large Washington technology employers post specifically for new graduates. Microsoft and Amazon both run structured new-graduate programs that place engineers into infrastructure and platform teams. Building a demonstrable portfolio, contributing to open-source MLOps frameworks, and earning a cloud associate certification are the credentials that most consistently separate early-career candidates in Washington screening processes.
Where can I find and apply to ai ml platform jobs in Washington?
You can find and apply to ai ml platform jobs in Washington on Migrate Mate, which lists current Washington openings. Find roles that fit your background and apply directly to the ones that match.
See All 5 AI ML Platform Jobs in Washington
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