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Mlops Engineer Jobs in Oregon (NOW HIRING)

Striim, Inc.

OR · On-site

$120K - $130K/yr

Working alongside experienced Solution Architects and Engineering teams, this role provides an ... Evaluate emerging technologies across AI, MLOps, cloud computing, and real-time data streaming.

New

Nike

Senior Principal Software Engineer

Beaverton, OR · On-site

$130K - $180K/yr

Experience with modern ML stacks (e.g., LLMs, PyTorch, TensorFlow, Spark, and cloud-native MLOps tools) * Strong track record with modern DevOps methodologies, automation, CI/CD pipelines, and ...

Juvare

Senior DevOps Engineer

OR · On-site +1

$129K - $166K/yr

... Engineer to help build, operate, and continuously improve the secure cloud platforms that power ... Experience supporting AI/MLOps workflows is a plus. Location * Atlanta / Remote Must Have * Cloud ...

Versapay

OR

$105K - $143K/yr

As a Senior Data Engineer, you will be pivotal in optimizing and scaling our foundational Snowflake ... Design and maintain MLOps pipelines to support the seamless rollout, monitoring, and lifecycle ...

LMI

The ML Ops Engineer will work at the intersection of advanced AI/ML development, machine learning ... Mentor junior team members, guiding their ML and MLOps skill development while contributing to ...

OneStudyTeam

Senior Machine Learning Engineer

OR · Remote

$140K - $190K/yr

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in ... Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy ...

Anno.ai

OR

$104K - $143K/yr

Due to the sensitive nature of our engineering work, Anno.ai enforces strict digital footprint and ... Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to ...

iHerb

OR

$122K - $161K/yr

Exposure to MLOps tooling or model deployment pipelines. * Contributions to internal developer ... tooling, golden path standards, or SDLC process improvements. * Experience with e-commerce ...

iHerb

OR

$114K - $137K/yr

This role will contribute to the company's data-driven culture, bring innovative approaches to cloud-native engineering, and help advance our MLOps capabilities to support production-grade AI/ML ...

New York Life

$55.75 - $74.50/hr

The engineer partners with the Cloud, Data & AI teams, Information Security, and Risk to ensure AI ... Support MLOps foundations such as: * Model deployment automation via Kubeflow, TensorFlow Extended ...

iHerb

OR

The Principal Engineer operates at the intersection of deep technical execution and broad ... MLOps experience: model deployment, monitoring, lifecycle management, and cost governance in a ...

Deloitte

AI Security Engineer Senior Manager

Portland, OR · On-site

$121K - $166K/yr

Architect Secure AI Solutions Guide secure architecture and engineering practices for AI/ML and GenAI platforms, integrating security into MLOps/LLMOps and DevSecOps pipelines. Drive Standards and ...

Aptive

MLOps and CI/CD automation * Cloud infrastructure and DevOps * Data lifecycle management * Risk and dependency management * Resource planning and forecasting * Executive reporting and stakeholder ...

Particle41

OR

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy ... Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker). * Strong ...

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All JobsMlops Engineer JobsMlops Engineer Jobs in Oregon

Mlops Engineer information

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

What is an MLOps Engineer job?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What engineers make $300,000 a year?

Senior MLOps engineers with extensive experience, advanced skills in machine learning deployment, cloud platforms, and automation tools can earn $300,000 or more annually. High compensation is often associated with specialized expertise, leadership roles, and working in competitive tech environments.

What engineers make $500,000?

Senior-level engineers in specialized fields such as software engineering, data engineering, and MLOps engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. Compensation often includes base salary, bonuses, and stock options, particularly in high-growth tech companies.

What are some common challenges Mlops Engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive in the Mlops Engineer position, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
What are the most commonly searched types of Mlops Engineer jobs in Oregon? The most popular types of Mlops Engineer jobs in Oregon are:
What are popular job titles related to Mlops Engineer jobs in Oregon? For Mlops Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Mlops Engineer jobs in Oregon look for? The top searched job categories for Mlops Engineer jobs in Oregon are:
What cities in Oregon are hiring for Mlops Engineer jobs? Cities in Oregon with the most Mlops Engineer job openings:
Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in Oregon as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
MLOps / AI Platform Engineer Subject Matter Expert

MLOps / AI Platform Engineer Subject Matter Expert

General Assembly

OR • Remote

$60 - $75/hr

Other

Posted 5 days ago

Job description

Company: General Assembly

Client: Confidential -  Customer Success Reskilling 

Start: ASAP

Hours: 15 to 20 hours a week, for 6 to 7 weeks (for a grand total of 90 to 140 hours) (Ends by July, 2026) (Most of your hours will be asynchronous - you will be vetting and iterating with our team - not building content from scratch yourselves.)

Compensation Range:  $60 - $75 per hour

Location: Remote

About the engagement

General Assembly is building a reskilling program for clients' Customer Success and Account Management professionals transitioning into MLOps and AI Platform Engineering roles. You'll serve as the subject matter expert for Pathway 3, validating the technical accuracy of pipeline content, governance frameworks, monitoring exercises, and async assets designed to bring CSAMs up to speed on taking AI systems from pilot to production at scale.

What you'll do

  • Review and validate competencies and learning objectives for the MLOps / AI Platform Engineer pathway
  • Validate technical accuracy of instructional slide content covering ML pipelines, model deployment, monitoring, and governance
  • Review async assets including prompt-alongs and self-paced exercises for technical correctness and appropriate difficulty level for the learner population (experienced customer-facing professionals, not engineers)
  • Participate in one structured SME review gate (approximately 1 week, early June)
  • Provide a single round of revision feedback for the LED to implement before QA

What you bring

  • 7+ years in software or data engineering with 3+ years in MLOps or ML platform roles in production
  • Hands-on experience with ML pipelines, model deployment, monitoring, and governance at scale
  • Strong DevOps and CI/CD fundamentals applied to ML workloads
  • Python proficiency, data engineering foundations, and Azure cloud infrastructure fluency
  • Familiarity with Azure ML, AI Foundry platform engineering patterns, and model lifecycle management
  • AZ-900, AI-900, and DP-100 minimum; AI-102 preferred
  • Former AI Platform or Azure ML engineer with Microsoft, Google, or similar company is a strong plus

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