AI Platform Engineer Jobs in Washington
AI Platform Engineer jobs in Washington are among the most active in the country, concentrated in cloud infrastructure, enterprise ML systems, and developer tooling across technology, aerospace, and healthcare sectors, with openings from early-career engineers through principal-level architects. Seattle and Bellevue anchor the market, with Redmond and Kirkland close behind, where employers like Microsoft, Amazon, and Boeing maintain deep engineering teams that regularly hire ai platform engineers. The most in-demand specialties include MLOps pipeline development, large language model infrastructure, and Kubernetes-based model serving platforms. Find a role that fits below and apply directly.
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Showing 5 of 25+ AI Platform Engineer jobs
- 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 (statutory, where applicable); 5 days/event (discretionary)
- 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: Kirkland, WA, USA; Sunnyvale, CA, USA.
Minimum qualifications:
- Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
- 6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
- 6 years of debug or validation experience with CPU, dGPU, or TPU
- 5 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
- Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
- Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
Preferred qualifications:
- Experience working with large-scale distributed systems, and familiarity with common solutions, design patterns, or best practices.
- Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
- Experience with systems automation, and with systems design and debug.
- Experience with ML frameworks (e.g., TensorFlow, Pytorch), and understanding of the AI/ML training and inference lifecycle.
- Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
- Understanding of memory and high-speed IO technologies.
About the job
Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Platform Application Engineer (Hardware Engineer), you will be focused on solving customer observations by, driving deep hardware analysis, debug, and issue resolution through to the root cause. You will dive deep into complex technical challenges, troubleshoot critical issues across the platform, and provide resolutions in both short-term and long-term platform solutions. In this role, you will represent the customer solution, collaborating tightly with engineering and product teams to drive continuous improvement in our products and services.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $188000 - $274000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
- Work closely with multiple Product, Quality, and Engineering teams to improve the product, and interact with our Site Reliability Engineering (SRE) teams to understand behaviors.
- Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
- Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
- 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 (statutory, where applicable); 5 days/event (discretionary)
- 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: Kirkland, WA, USA; Sunnyvale, CA, USA.
Minimum qualifications:
- Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
- 6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
- 6 years of debug or validation experience with CPU, dGPU, or TPU
- 5 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
- Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
- Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
Preferred qualifications:
- Experience working with large-scale distributed systems, and familiarity with common solutions, design patterns, or best practices.
- Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
- Experience with systems automation, and with systems design and debug.
- Experience with ML frameworks (e.g., TensorFlow, Pytorch), and understanding of the AI/ML training and inference lifecycle.
- Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
- Understanding of memory and high-speed IO technologies.
About the job
Our AI Infrastructure Engineering Support team is dedicated to ensuring our customers get the most out of their Google Cloud hardware investment. As a Platform Application Engineer (Hardware Engineer), you will be focused on solving customer observations by, driving deep hardware analysis, debug, and issue resolution through to the root cause. You will dive deep into complex technical challenges, troubleshoot critical issues across the platform, and provide resolutions in both short-term and long-term platform solutions. In this role, you will represent the customer solution, collaborating tightly with engineering and product teams to drive continuous improvement in our products and services.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $188000 - $274000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity on AI/ML infrastructure.
- Work closely with multiple Product, Quality, and Engineering teams to improve the product, and interact with our Site Reliability Engineering (SRE) teams to understand behaviors.
- Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
- Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
See All 25 AI Platform Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI Platform Engineer JobsAI Platform Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
AI Platform 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
What Washington Employers Look For
The qualifications that appear most often in AI platform engineer 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 pipelines using tools such as Kubeflow, MLflow, or Apache Airflow
- Proficiency in Python and at least one cloud platform, with Azure and AWS most prevalent in Washington listings
- Experience containerizing and orchestrating workloads with Docker and Kubernetes in production environments
- Familiarity with LLM serving infrastructure, model registries, and vector database integrations
- Strong collaboration skills for working across data science, DevOps, and product teams in cross-functional settings
AI Platform Engineer Jobs in Washington: Frequently Asked Questions
How do you become a ai platform engineer in Washington?
Washington does not require a state-issued license to work as an ai platform engineer. The typical path starts with a bachelor's degree in computer science, software engineering, or data engineering, followed by hands-on experience with cloud platforms and ML tooling. Employers in Washington's technology corridor strongly favor candidates with demonstrated project work in MLOps or model deployment, and cloud certifications from AWS, Azure, or Google Cloud give candidates a concrete edge in local listings.
How much do AI platform engineers make in Washington?
AI platform engineers in Washington earn a median of about $128,940 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $60,210 for the lowest 10% to over $200,610 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai platform engineers in Washington?
Employers hiring ai platform engineers in Washington right now include Amazon, GEICO, and Apple, based on current listings on Migrate Mate as of September 2026. Washington's concentration of major cloud and enterprise technology headquarters means openings frequently appear at both household-name technology companies and the aerospace and defense contractors that rely on ML infrastructure for engineering and operations workloads.
Which Washington cities have the most ai platform engineer jobs?
Seattle, Bellevue, and Redmond have the most ai platform engineer openings in Washington. Seattle and Bellevue dominate because they host the global headquarters and major engineering campuses of the state's largest technology employers, while Redmond draws steady demand from Microsoft's sprawling product and cloud divisions, and Kirkland and Bothell contribute openings from mid-size technology and life sciences firms that have expanded along the Eastside corridor.
Are there remote ai platform engineer jobs in Washington?
Yes, and more than most fields. About 63% of ai platform engineer openings tied to Washington are remote or hybrid as of September 2026, reflecting how well-suited the role is to distributed engineering teams. The portions of the work most commonly done remotely include pipeline development, model experimentation, and infrastructure-as-code, while on-site presence is more often expected for roles tied to regulated data environments or on-premises GPU clusters.
How can I get hired as a ai platform engineer in Washington with little or no experience?
The most realistic entry path is through a software engineering or data engineering role at a Washington technology company, then moving laterally into platform work as teams adopt ML infrastructure. Amazon, Microsoft, and Boeing all run new-graduate rotational and associate engineering programs that include cloud and data infrastructure tracks. Building a public portfolio of MLOps projects on open datasets, earning an Azure or AWS cloud certification, and targeting roles titled junior ML engineer or data platform engineer at Eastside technology firms gives early-career candidates the strongest footing.
Where can I find and apply to ai platform engineer jobs in Washington?
You can find and apply to ai platform engineer jobs in Washington on Migrate Mate, which lists current Washington openings across Seattle, Bellevue, Redmond, and other hiring centers in the state. Find the roles that fit your experience and apply directly to the ones that match.
See All 25 AI Platform Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI Platform Engineer Jobs