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Mlops Jobs in Oregon (NOW HIRING)

Atos

Head of AI

OR · On-site +1

This executive role owns practice P&L, builds scalable offerings (GenAI, ML, data science, AI platforms, MLOps), and partners with sales and delivery leaders to expand revenue and customer impact ...

SentinelOne

Sr. Manager, AI Software Engineering

OR · On-site +1

Help define and enforce best practices for AI system development, MLOps, service reliability, security, and performance. * Support architecture and design decisions for scalable, low-latency, highly ...

Robots and Pencils

Principal AI Architect

OR · On-site +1

Design AI/ML systems including model serving, MLOps pipelines, feature stores, and LLM-based applications (e.g., SageMaker, Vertex AI, MLflow, Hugging Face) * Define infrastructure as code, CI/CD ...

Robots and Pencils

Principal AI Architect

OR · On-site +1

Design AI/ML systems including model serving, MLOps pipelines, feature stores, and LLM-based applications (e.g., SageMaker, Vertex AI, MLflow, Hugging Face) * Define infrastructure as code, CI/CD ...

Nvidia

Machine Learning Engineer, AI Safety

OR · On-site +1

Follow the best MLOps practices of automation, monitoring, scale and safety. Contribute to the MLOps platform and develop safety tools to help ML teams be more effective. Collaborate with other ...

Tebra

Data Engineer

OR · On-site +1

$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 ...

Dataiku

Sr Technical Account Manager - West

OR · On-site +1

Support innovative approaches around Dataiku (edge computing, deep learning, advanced MLOps, for example) What you'll need to be successful * 7+ years of experience in a customer facing technical ...

Dataiku

Sr Technical Account Manager - East

OR · On-site +1

Support innovative approaches around Dataiku (edge computing, deep learning, advanced MLOps, for example) What you'll need to be successful * 7+ years of experience in a customer facing technical ...

SentinelOne

Senior Backend Software Engineer, ObservoAI

OR · On-site +1

$122K - $161K/yr

Deep expertise in database technologies (SQL and NoSQL) and advanced experience with machine learning frameworks (TensorFlow, PyTorch) and MLOps practices for production ML systems. * Expert ...

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Showing results 21-40

All JobsMlops JobsMlops Jobs in Oregon

Mlops information

See Oregon salary details

$101.2K

$158.9K

$189K

How much do mlops jobs pay per year?

As of Sep 6, 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.

Senior Solutions Architect / Senior Solutions Engineer (Commercial)

OpenTeams

OR • On-site, Remote

$55.25 - $71.25/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 15 days ago

Job description

About the Role

OpenTeams is seeking several highly experienced and visionary Senior Solution Architects and/or Senior Solution Engineers (Sales) to join our growing team. In this pivotal role, you will be a trusted partner with our general managers working directly with our clients and leading the ideation, design and/or implementation of complex, large-scale open-source AI solutions. You will leverage your expertise in AI/ML, data science, cloud/on-prem platforms, and open-source technologies to translate business requirements into technical architectures, guide development teams, and ensure successful project delivery. This role offers the unique opportunity to shape the future of AI adoption across diverse organizations and contribute to the vibrant open-source community.

What You'll Do

Specific responsibilities will vary depending on experience and interest but will be drawn from the following areas:

  • Solution Leadership: Lead the end-to-end architectural design and technical strategy for complex open-source AI solutions, from initial concept to deployment and optimization.
  • Client Engagement: Act as a primary technical point of contact for clients, understanding their business challenges, identifying opportunities for AI innovation, and effectively communicating technical concepts to both technical and non-technical stakeholders.
  • Technical Advisory: Provide expert guidance and recommendations on open-source AI frameworks, libraries, tools, and platforms (e.g., PyTorch, JAX, Kubeflow, Ray, MCP and relevant open-source LLMs etc).
  • Architecture Definition: Develop comprehensive architectural blueprints, including data pipelines, model training and deployment strategies, MLOps practices, security considerations, and integration patterns.
  • Pre-Sales Support: Collaborate with the sales and business development teams to articulate OpenTeams' capabilities, present technical solutions, and contribute to proposals and statements of work.
  • Thought Leadership: Stay abreast of the latest advancements in open-source AI, contribute to technical blogs, whitepapers, and presentations, and represent OpenTeams at industry conferences and events.
  • Community Engagement: Actively participate in and contribute to relevant open-source projects and communities surrounding AI & ML.
  • Risk Management: Identify and mitigate technical risks throughout the project lifecycle.

What We're Looking For

  • Open Source Expertise: Deep practical experience with a wide range of open-source AI frameworks, libraries, and tools with an emphasis on AI/ML 
  • Software Engineering: Strong background in software engineering principles, design patterns, and best practices. Proficiency in Python is essential.
  • Communication: Exceptional verbal and written communication skills, with the ability to articulate complex technical concepts clearly to diverse audiences.
  • Problem-Solving: Proven ability to analyze complex technical problems, propose innovative solutions, and drive them to successful implementation.
  • Leadership: Strong leadership, mentoring, and interpersonal skills. Ability to work effectively with cross-functional teams.
  • Technical Experience: Deep technical expertise in at least one core area and sound understanding of several other areas: Numerical Computing, Distributed & High-Performance Computing, Infrastructure/Cloud, Data Science/Machine Learning, MLOps, Data Engineering, Generative AI, Agentic AI, LLMs etc.

Bonus Points

  • Significant contributions to open-source AI or Scientific Python/PyData ecosystem (e.g., code contributions, active maintainership, leadership roles).
  • Active participation and contributions to the Open Source communities (e.g., presenting at conferences, organizing meetups, contributing to libraries like PyTorch, NumPy etc).
  • Previous experience in a consulting role is highly desirable.
  • Prior experience working with government agencies or on government contracts.
  • Existing U.S. government security clearance or the willingness and ability to obtain one.

What We Offer

  • Medical, Dental & Vision - 100% paid for employees, 75% for dependents
  • 401(k) Match - Up to 5% with full vesting after 2 years
  • Unlimited PTO - With a required minimum of 15 days off annually
  • Fully Remote Setup - Includes up to $3,000 equipment reimbursement
  • Continuous Education -  Includes up to $500 reimbursement
  • Disability & Life Insurance - 100% employer-paid
  • HSA & FSA Options - With monthly HSA contributions from OpenTeams

Why Join OpenTeams?

  • Impactful Work: Work on cutting-edge AI projects that solve real-world problems for a diverse range of clients while ensuring intelligence remains distributed and sovereign
  • Open Source Focus: Be at the forefront of open-source AI innovation and contribute to the community.
  • Collaborative Environment: Join a team of passionate and talented individuals who are dedicated to mutual success and continuous learning.
  • Growth Opportunities: Continuous learning and professional development opportunities in a rapidly evolving field.

Apply