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Mlops Jobs in Oregon (NOW HIRING)

Saksoft

MLOPS Engineer

Portland, OR · On-site

MLOPS ENGINEER JD: This data science role requires a minimum of 7 years of Python and data science experience, 3 years of AWS experience, and hands-on delivery of machine learning and Generative AI ...

Dataiku

Product Marketing Manager

OR · On-site +1

$153K/yr

As Product Marketing Manager for Analytics & MLOps, you will own the go-to-market for two of Dataiku's most established product surfaces: the visual analytics and data preparation capabilities that ...

OneStudyTeam

Senior Machine Learning Engineer

OR · On-site +1

$140K - $190K/yr

Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy models at scale. You'll use technologies like Python (and Clojure), AWS services (Athena, Bedrock ...

Anno.ai

Senior Machine Learning Engineer

OR · On-site +1

$104K - $143K/yr

Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, extensibility, scalability, and deployment speed of ML systems Required ...

phData

Applied AI Solutions Architect

OR · On-site +1

$63 - $83/hr

Lead the design of end-to-end Applied AI architectures that span predictive ML, MLOps, generative AI, LLM applications, agentic workflows, and intelligent automation aligned to client objectives and ...

Natera

Director of Data Science and Bioinformatics

OR · On-site +1

Implement MLOps tooling and automated validation frameworks to support reliable algorithm deployment into clinical production. Cross-Functional Collaboration * Partner with Research, Product ...

NICE

Manager, Client Services, AI, CX

OR · On-site +1

Partner with Data/ML Engineering, MLOps, Security, and Business stakeholders. People Leadership * Lead, mentor, and coach PMs, TPMs, and analysts. * Manage staffing, workload balancing, and ...

SentinelOne

Principal AI Engineering Architect

OR · On-site +1

Oversee the establishment of best practices for MLOps, security, and performance monitoring to ensure the reliability and efficacy of our AI defense mechanisms. What Skills and Knowledge Will You ...

CookUnity

Senior Data Scientist, Retention & Product

OR · On-site +1

Production & MLOps: Own the full model lifecycle and ship models into the systems where they act; handle monitoring, retraining, and drift. * Experimentation & incrementality: Design experiments and ...

WEKA

Partner ISV Alliances Manager

OR · On-site +1

$82K - $82K/yr

Identify and develop joint opportunities where multiple ISV relationships intersect - particularly where orchestration, MLOps, and inference platforms converge on shared infrastructure - and align ...

New

Nvidia

Senior Applied AI Engineer, Cybersecurity

OR · On-site +1

$114K - $156K/yr

Take AI capabilities from experimentation to production using strong software engineering and MLOps/LLMOps practices. Build continuous evaluation, observability, versioning, controlled deployment ...

WEKA

Partner ISV Alliances Manager

OR · On-site +1

$82K - $82K/yr

Identify and develop joint opportunities where multiple ISV relationships intersect - particularly where orchestration, MLOps, and inference platforms converge on shared infrastructure - and align ...

New

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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 5, 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.

MLOPS Engineer

Saksoft

Portland, OR • On-site

Other

Posted 4 days ago

Job description

MLOPS ENGINEER

JD:

This data science role requires a minimum of 7 years of Python and data science experience, 3 years of AWS experience, and hands-on delivery of machine learning and Generative AI use cases. 

Core Technical Requirements

• Data Science: Minimum 7 years of hands-on coding and model development in Python. 
• Cloud Infrastructure: Minimum 3 years of production experience working within the AWS ecosystem. 
• Machine Learning: Proven background in machine learning with at least 5 distinct, well-documented use cases covering a mix of classification, regression, or forecasting models. 
• Generative AI: Demonstrated delivery of at least 2 Generative AI use cases (Preferred candidates with: keywords such as multimodal applications, image-plus-text processing, or advanced model fine-tuning in GenAI use cases)

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