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Mlops Engineer Jobs in Portland, OR (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 ...

New

Deloitte

AI Engineer Consultant

Portland, OR · Hybrid

... LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

A-dec, Inc.

AI Engineer, Sr

Newberg, OR

$109K - $150K/yr

Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial ... Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management

A-dec, Inc.

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial ... Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management

SupportFinity™

AI Engineer, Sr

Newberg, OR · On-site

$140 - $220/hr

Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial ... Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management

Deloitte

Lead Forward Deployed Engineer - AWS

Portland, OR · On-site

$108K - $143K/yr

Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

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Mlops Engineer information

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 do you need to be a MLOps engineer?

To become a MLOps engineer, you typically need a strong background in software engineering, machine learning, and cloud platforms. Proficiency in programming languages like Python, experience with containerization tools such as Docker, and knowledge of CI/CD pipelines are essential. Certifications in cloud services and familiarity with tools like Kubernetes and ML frameworks also enhance qualifications.

Who earns more, ML engineer or MLOps engineer?

MLOps engineers typically earn slightly more than ML engineers due to their focus on deploying, maintaining, and scaling machine learning systems, which requires expertise in cloud platforms, automation, and infrastructure. Salary differences can vary based on experience, location, and company size, but MLOps roles often command higher compensation because of their specialized skill set.

What are popular job titles related to Mlops Engineer jobs in Portland, OR?

For Mlops Engineer jobs in Portland, OR, the most frequently searched job titles are:

What job categories do people searching Mlops Engineer jobs in Portland, OR look for?

The top searched job categories for Mlops Engineer jobs in Portland, OR are:

Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in Portland, OR as of August 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

MLOPS Engineer

Saksoft

Portland, OR • On-site

Other

Posted 2 days ago

New

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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