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Ai Reliability Engineer Jobs in Seattle, WA (NOW HIRING)

SRE Engineer -AI

Redmond, WA · On-site

$63.75 - $84.75/hr

Job Title : SRE Engineer Location: Redmond,WA Duration: 6 Months Experience: 10-22 Years Description: Responsibilities: Deploy and manage AI resources on Microsoft Azure, including AI Foundry and RAG ...

SRE Engineer

Redmond, WA · On-site

$63.75 - $84.75/hr

Deploy and manage AI resources on Microsoft Azure, including AI Foundry and RAG solutions * Monitor and ensure service uptime, availability, reliability, and latency * Track and integrate SRE metrics ...

Define and lead WEX's AI-Powered Reliability Engineering strategy, driving adoption of SRE agents across the software lifecycle-from design and development through deployment and operations, to ...

Define and lead WEX's AI-Powered Reliability Engineering strategy, driving adoption of SRE agents across the software lifecycle-from design and development through deployment and operations, to ...

We are looking for an experienced SRE leader with the skills and passion to make a significant ... AI Developer Tools: Lead the standardization of AI developer assistants by architecting and ...

Site Reliability Engineer

Seattle, WA · On-site

$152K - $219K/yr

Meet the Team The SRE Fleet team is responsible for maintaining the stability, scalability, and ... Experience leveraging AI-assisted development tools to improve software development, automation ...

We are looking for an experienced SRE leader with the skills and passion to make a significant ... AI Developer Tools: Lead the standardization of AI developer assistants by architecting and ...

Principal Site Reliability Engineer

Bellevue, WA · On-site

$64.25 - $85.50/hr

We are looking for an experienced SRE leader with the skills and passion to make a significant ... AI Developer Tools: Lead the standardization of AI developer assistants by architecting and ...

About Nscale Nscale is the GPU cloud built for AI. We run high-performance, cost-efficient ... The Role This is a career-level SRE role for someone who wants to own systems, not just watch them.

Site Reliability Engineer

Seattle, WA

$64.75 - $86.25/hr

Position Overview SingleStore is seeking a Site Reliability Engineer to help optimize and scale our ... AI applications on a unified data platform that supports real-time transactions, analytics, and ...

Site Reliability Engineer

Seattle, WA

$64.75 - $86.25/hr

Position Overview SingleStore is seeking a Site Reliability Engineer to help optimize and scale our ... AI applications on a unified data platform that supports real-time transactions, analytics, and ...

Site Reliability Engineer

Seattle, WA · On-site

$64.75 - $86.25/hr

Position Overview SingleStore is seeking a Site Reliability Engineer to help optimize and scale our ... AI applications on a unified data platform that supports real-time transactions, analytics, and ...

Principal SRE

Seattle, WA · On-site

$180K - $240K/yr

The Role As a Principal Site Reliability Engineer at Gradial, you will shape the foundation our ... Nice to Have * Familiarity with AI or ML infrastructure, including GPU provisioning, model ...

Sr. SRE Consultant

Seattle, WA · On-site

$64.75 - $86.25/hr

Role: Sr. SRE (Very Strong Technical SRE) Location: Seattle, WA WFO: Mandatory (3 days/week) Short ... The company specializes in Business and Management Consulting, AI/ML, Data Analytics ...

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Showing results 1-20

Ai Reliability Engineer information

See Seattle, WA salary details

$69.4K

$134.3K

$160.5K

How much do ai reliability engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for ai reliability engineer in Seattle, WA is $134,256.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,600.00 and $146,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Reliability Engineer, and why are they important?

To thrive as an AI Reliability Engineer, you need a solid background in computer science or engineering, expertise in AI/ML concepts, and experience with software testing and reliability methodologies. Familiarity with tools like TensorFlow, PyTorch, CI/CD pipelines, and reliability testing frameworks, along with certifications in cloud platforms (e.g., AWS Certified Machine Learning), is highly valuable. Analytical thinking, problem-solving abilities, and strong collaboration skills set top performers apart in this role. These skills ensure robust, dependable AI systems that meet performance standards and maintain trust in critical applications.

What is the difference between Ai Reliability Engineer vs Data Scientist?

AspectAi Reliability EngineerData Scientist
Required CredentialsBachelor's or master's in CS, engineering, or related; certifications in AI/MLBachelor's or master's in CS, statistics, or related; certifications in data analysis or ML
Work EnvironmentTech companies, AI-focused teams, engineering departmentsResearch labs, tech firms, analytics teams
Employer & Industry UsageAI product development, machine learning systems, reliability testingData analysis, predictive modeling, business insights

While both roles involve AI and ML, Ai Reliability Engineers focus on ensuring AI system robustness and uptime, whereas Data Scientists analyze data to generate insights and models. The roles often collaborate but serve different primary functions within AI projects.

What are AI Reliability Engineers?

AI Reliability Engineers are professionals responsible for ensuring that artificial intelligence systems function reliably, safely, and effectively over time. They work on monitoring AI models in production, identifying and mitigating potential failures, and improving the robustness of AI systems. Their tasks often include testing, validation, performance monitoring, and implementing best practices for maintaining AI infrastructure. By focusing on reliability, they help organizations deploy AI solutions that are dependable and trustworthy in real-world environments.

What are some common challenges Ai Reliability Engineers face when ensuring model robustness in production environments?

Ai Reliability Engineers often encounter challenges such as monitoring AI model performance for drift or unexpected behavior, managing data quality issues, and implementing automated alerting systems for anomalies. In production, it's crucial to ensure that AI models operate consistently and remain reliable under varying conditions and data inputs. Collaborating closely with data scientists, software engineers, and DevOps teams is essential to address these challenges and to continuously improve model reliability and uptime.
What are popular job titles related to Ai Reliability Engineer jobs in Seattle, WA? For Ai Reliability Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Ai Reliability Engineer jobs in Seattle, WA look for? The top searched job categories for Ai Reliability Engineer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Ai Reliability Engineer jobs? Cities near Seattle, WA with the most Ai Reliability Engineer job openings:
Infographic showing various Ai Reliability Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $134,256 per year, or $64.5 per hour.
SRE Engineer -AI

SRE Engineer -AI

iFlow Inc

Redmond, WA • On-site

$63.75 - $84.75/hr

Contractor

Posted 2 days ago


Job description


Job Title:  SRE Engineer 
Location:Redmond,WA 
Duration:6 Months
Experience:10-22 Years
Description:
Responsibilities:
Deploy and manage AI resources on Microsoft Azure, including AI Foundry and RAG solutions
Monitor and ensure service uptime, availability, reliability, and latency
Track and integrate SRE metrics with enterprise monitoring systems
Support CI/CD and DevOps workflows using GitHub and Azure DevOps
Skills Required:
Good experience with Azure and Azure AI services
Knowledge of SRE principles and monitoring metrics
Hands-on experience with GitHub CLI, Repos, Azure DevOps
Basic C# knowledge