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Mlops Jobs in Oregon (NOW HIRING)

Particle41

AI Engineer

OR · On-site +1

Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker). * Strong understanding of algorithms, data structures, statistics, and machine-learning fundamentals (classification ...

Attain Talent

Lead AI/ML Engineer

OR · On-site +1

$180K - $230K/yr

Experience deploying AI solutions using MLOps best practices. * Experience with containerization technologies such as Docker and Kubernetes. * Experience building CI/CD pipelines for AI/ML workloads.

Munich Re

Sr. Solution Architect

Bend, OR · On-site

Define and govern enterprise AI architecture standards , including model lifecycle management, MLOps, and AI platform integration. * Ensure responsible and compliant AI adoption, aligned with AI ...

Robots and Pencils

VP, Solutions Architect - AWS

OR · On-site +1

$64.75 - $85/hr

Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config. * Define governance, responsible ...

Robots and Pencils

Senior Solutions Architect

OR · On-site +1

Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config. * Define governance, responsible ...

NewRocket

AI Platform Engineer-Anthropic-US West

OR · On-site +1

This role combines cloud engineering, platform engineering, DevOps, MLOps/LLMOps, data-platform integration, and applied AI engineering. The AI Platform Engineer will work closely with AI Architects ...

Munich Re

Sr. Solution Architect

Eugene, OR · On-site

Define and govern enterprise AI architecture standards , including model lifecycle management, MLOps, and AI platform integration. * Ensure responsible and compliant AI adoption, aligned with AI ...

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Mlops information

See Oregon salary details

$101.2K

$158.9K

$189K

How much do mlops jobs pay per year?

As of Sep 6, 2026, the average yearly pay for mlops in Oregon is $158,874.00, according to ZipRecruiter salary data. Most workers in this role earn between $150,110.00 and $172,551.00 per year, depending on experience, location, and employer.

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What are the key skills and qualifications needed to thrive as an MLOps engineer?

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

Is MLOps outdated?

MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.

What is the average salary in MLOps?

The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.

What are the most commonly searched types of Mlops jobs in Oregon?

The most popular types of Mlops jobs in Oregon are:

What are popular job titles related to Mlops jobs in Oregon?

For Mlops jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Mlops jobs in Oregon look for?

The top searched job categories for Mlops jobs in Oregon are:

What cities in Oregon are hiring for Mlops jobs?

Cities in Oregon with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Oregon as of August 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $158,874 per year, or $76.4 per hour.

Enterprise Architect - Data, AI

Fisher Investments Careers

Portland, OR • On-site

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

It's an exciting time to join Fisher Investments! We're continuing to invest in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled global team that inspires future scale through strategic solutions, innovation, mentoring, and tight knit teamwork. The Opportunity: The Enterprise Architect will bring strong cross‑domain expertise, strategic thinking, and executive presence. This is not just a governance‑only role. You will BE a strategic leader, facilitator, and a diplomat—someone who can influence CXO‑level stakeholders and remain deeply involved in execution. You will work across domains to lead enterprise‑wide architecture decisions that prepare us for scalable data and AI modernization. In an individual contributor role, you will work in a fast‑moving, mid‑size, highly collaborative environment. You will report to the Vice President, Enterprise Architecture and Standards. The Day-to-Day: * Drive enterprise‑level architecture across multiple business domains, ensuring alignment with organizational strategy * Lead discussions with senior stakeholders and bring clarity to complex technical decisions * Lead the standardization of metadata practices across domains, ensuring discoverability, lineage, and governance * Design and evolve enterprise-level semantic data models, including logical and conceptual models, ontologies, and domain definitions * Partner with product, engineering, data, and AI teams to ensure data supports reporting, analytics, and AI use cases * Provide feedback that directly shapes the next generation of AI models * Knowledge of Machine Learning Operations (MLOps) workflows and tools for deploying, managing, and monitoring AI models in production * Actively participate in design, discussions, and delivery—not just governance—with hands‑on engagement * Review AI-generated code to ensure it is accurate, efficient, and high quality. * Stay current on AI and data trends to help the organization evolve. Your Qualifications: * 15+ years of experience in IT * 5+ years of experience: * In an Enterprise Architect role * AI and ML Architectures * 2+ years of experience: * Data-focused A1 tools * Lead Enterprise Architecture initiatives * Proficient in tools such as Purview, Unity catalog, Erwin, or other semantic/metadata platforms * Deep experience with Microsoft Azure and their AI and data services * Experience working with Financial Services Industry * Bachelor's degree in computer science, Information Systems, Engineering, or equivalent experience through work experience Compensation: * $200,000 - $240,000 base salary per year in the state of WA. New hires should expect to start at the lower end of the range depending on experience * Eligible for a discretionary bonus based on firm and individual performance Why Fisher Investments: We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: * 100% paid medical, dental and vision premiums for you and your qualifying dependents * A 50% 401(k) match, up to the IRS maximum * 20 days of PTO, plus 10 paid holidays * Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care * This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER

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