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Mlops Engineer Jobs in Oregon (NOW HIRING)

The Avian Consulting LLC

MLOps Engineer

Portland, OR · On-site

MLOps Engineer Location: Portland, OR (Complete Onsite) Note: Client Interview Face to Face Key Responsibilities * Design, build, and maintain end-to-end MLOps pipelines for model training, testing ...

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.

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 · On-site

$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 · On-site

$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 · On-site

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 ...

Tebra

Data Engineer

OR · Remote

$114K - $137K/yr

Collaborate with ML Engineers and cross-functional partners to support MLOps best practices, including data versioning, lineage, and reproducibility. * Break down technical work into manageable tasks ...

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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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?

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 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 as an MLOps engineer, 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 August 2026, with employment types broken down into 43% Full Time, 5% Temporary, and 52% Contract. Highlights an 62% In-person, and 38% Remote job distribution.

MLOps Engineer

The Avian Consulting LLC

Portland, OR • On-site

Other

Posted 4 days ago

Job description

Position: MLOps Engineer
Location: Portland, OR (Complete Onsite)
Note: Client Interview Face to Face
Job Description:

Key Responsibilities

  • Design, build, and maintain end-to-end MLOps pipelines for model training, testing, deployment, and monitoring.

  • Automate ML workflows using CI/CD best practices.

  • Deploy and manage machine learning models in production environments.

  • Develop scalable data and model pipelines on cloud platforms.

  • Monitor model performance, data drift, and system health.

  • Collaborate with data scientists to productionize ML models.

  • Implement model versioning, experiment tracking, and artifact management.

  • Optimize infrastructure for performance, scalability, and cost efficiency.

  • Ensure security, governance, and compliance for ML platforms.

  • Troubleshoot production issues and improve operational reliability.

Required Skills

  • 5+ years of experience in DevOps, Data Engineering, or MLOps.

  • Strong experience with Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

  • Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.

  • Experience with containerization technologies like Docker and Kubernetes.

  • Strong knowledge of CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.

  • Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).

  • Experience with Infrastructure as Code tools such as Terraform or CloudFormation.

  • Knowledge of model monitoring, logging, and observability tools.

  • Strong understanding of Git version control and software development best practices.

  • Experience with Linux environments and shell scripting.

Preferred Qualifications

  • Experience with Generative AI, LLM deployment, or RAG-based applications.

  • Familiarity with Apache Airflow, Kafka, or Spark.

  • Knowledge of feature stores and model registries.

Apply