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Mlops Data 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 ...

Deloitte

AI Engineer Consultant

Portland, OR · Hybrid

... and HR data domains. * 2+ years of experience operationalizing LLMOps/MLOps capabilities ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

Deloitte

Lead Forward Deployed Engineer - AWS

Portland, OR · On-site

$108K - $143K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Deloitte

Senior Forward Deployed Engineer- AWS

Portland, OR · On-site

$110K - $152K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Deloitte

Forward Deployed Engineer- AWS

Portland, OR · On-site

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Design end-to-end ML pipelines including Data ingestion, feature engineering, model training ... MLOps practices (CI/CD, monitoring, model versioning) * Knowledge of: * Signal processing or ...

A-dec, Inc.

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Implement data pipelines and feature engineering processes to support reliable model training and ... Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management

A-dec, Inc.

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Implement data pipelines and feature engineering processes to support reliable model training and ... Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management

SupportFinity™

AI Engineer, Sr

Newberg, OR · On-site

$140 - $220/hr

Implement data pipelines and feature engineering processes to support reliable model training and ... Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management

HR Tech Job

Sr Software Development Engineer

Beaverton, OR · On-site

$177.86 - $234/hr

Two (24) months of experience in algorithms and data structures. * Two (24) months of experience in ... Two (24) months of experience in MLOps. * Two (24) months of experience in CI/CD pipelines such as ...

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All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Portland, OR

Mlops Data Engineer information

See Portland, OR salary details

$47.2K

$137.6K

$188.2K

How much do mlops data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for mlops data engineer in Portland, OR is $137,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,400.00 and $145,800.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

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

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

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

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

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

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

What cities near Portland, OR are hiring for Mlops Data Engineer jobs?

Cities near Portland, OR with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Portland, OR as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $137,565 per year, or $66.1 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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