ZipRecruiter

Log In

1

Mlops Data Engineer Jobs in Portland, OR (NOW HIRING)

Nike

Senior Principal Software Engineer

Beaverton, OR · On-site

$130K - $180K/yr

Hands-on experience with modern data platform technologies (e.g., Databricks, Snowflake, Kafka ... Experience with modern ML stacks (e.g., LLMs, PyTorch, TensorFlow, Spark, and cloud-native MLOps ...

Honor

Staff Data Scientist

Portland, OR · Remote

Partner closely with Engineering, PM, and Care Operations to collaboratively define strategy and ... Familiarity with modern MLOps practices, cloud platforms (AWS), containerization (Docker), or CI/CD ...

Munich Re

Data and AI Enterprise Architect

Gresham, OR · On-site

... management, MLOps, and AI platform integration. * Ensure responsible and compliant AI adoption ... Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure ...

previous pagenext page

Showing results 21-40

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 Aug 23, 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.

Enterprise Architect - Data, AI

Fisher Investments

Portland, OR • Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 days ago

Fisher Investments rating

8.5

Company rating: 8.5 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

Job description

It's an exciting time to join Fisher Investments! We're continuing to invest in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled global team that inspires future scale through strategic solutions, innovation, mentoring, and tight knit teamwork.

The Opportunity:

 

The Enterprise Architect will bring strong cross‑domain expertise, strategic thinking, and executive presence. This is not just a governance‑only role. You will BE a strategic leader, facilitator, and a diplomat—someone who can influence CXO‑level stakeholders and remain deeply involved in execution. You will work across domains to lead enterprise‑wide architecture decisions that prepare us for scalable data and AI modernization. In an individual contributor role, you will work in a fast‑moving, mid‑size, highly collaborative environment. You will report to the Vice President, Enterprise Architecture and Standards.

The Day-to-Day:

  • Drive enterprise‑level architecture across multiple business domains, ensuring alignment with organizational strategy
  • Lead discussions with senior stakeholders and bring clarity to complex technical decisions
  • Lead the standardization of metadata practices across domains, ensuring discoverability, lineage, and governance
  • Design and evolve enterprise-level semantic data models, including logical and conceptual models, ontologies, and domain definitions
  • Partner with product, engineering, data, and AI teams to ensure data supports reporting, analytics, and AI use cases
  • Provide feedback that directly shapes the next generation of AI models
  • Knowledge of Machine Learning Operations (MLOps) workflows and tools for deploying, managing, and monitoring AI models in production
  • Actively participate in design, discussions, and delivery—not just governance—with hands‑on engagement
  • Review AI-generated code to ensure it is accurate, efficient, and high quality.
  • Stay current on AI and data trends to help the organization evolve.

Your Qualifications:

  • 15+ years of experience in IT
  • 5+ years of experience:
    • In an Enterprise Architect role
    • AI and ML Architectures
  • 2+ years of experience:
    • Data-focused A1 tools
    • Lead Enterprise Architecture initiatives
  • Proficient in tools such as Purview, Unity catalog, Erwin, or other semantic/metadata platforms
  • Deep experience with Microsoft Azure and their AI and data services
  • Experience working with Financial Services Industry
  • Bachelor’s degree in computer science, Information Systems, Engineering, or equivalent experience through work experience

Compensation:

  • $200,000 - $240,000 base salary per year in the state of WA. New hires should expect to start at the lower end of the range depending on experience
  • Eligible for a discretionary bonus based on firm and individual performance

Why Fisher Investments:

We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like:

  • 100% paid medical, dental and vision premiums for you and your qualifying dependents
  • A 50% 401(k) match, up to the IRS maximum
  • 20 days of PTO, plus 10 paid holidays
  • Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care
  • This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. 

FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER

What Fisher Investments employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply