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Mlops Machine Learning Engineer Jobs in Oregon (NOW HIRING)

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$113K - $188K/yr

As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Operationalize machine learning models built by data science teams and ensure production readiness

OR · On-site

Strong programming (Python, Golang) and algorithmic skills. * Solid foundations in machine learning, algorithms, or optimization * Curious, self-motivated, and comfortable working on open-ended ...

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs. Current focus areas include:

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs. Current focus areas include:

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$122.40K - $161.30K/yr

... Engineering, Mathematics, or a related field. * 8+/7+ years of professional work experience after BS/MS applying machine learning to real-world problems, and crafting scalable and effective ML/AI ...

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$66.25 - $80/hr

Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on ... You will implement best-in-class MLOps practices for monitoring, continuous integration/continuous ...

Principal Machine Learning Engineer, Agentic AI

OR · On-site +1

$204.40K - $326.60K/yr

As a Principal Machine Learning Engineer on the Agentic AI team, you will: * Leverage frameworks like AgentSDK, and LangChain/LangGraph to design, prototype, and develop multi-agent systems that are ...

OR

$205K - $355K/yr

Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform * Collect and gather ...

OR

$104.40K - $143.40K/yr

About the role We are looking for a Senior Machine Learning Engineer, Voice Experience to help build the next generation of AI-powered voice systems for the contact center. In this role, you will ...

Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, playbooks, and training related to machine learning engineering and MLOps. * Represent ...

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Mlops Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps Machine Learning Engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What does an MLOps Machine Learning Engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Oregon? For Mlops Machine Learning Engineer jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Mlops Machine Learning Engineer jobs? Cities in Oregon with the most Mlops Machine Learning Engineer job openings:

$113K - $188K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 8 days ago


Guidehouse rating

7.5

Company rating: 7.5 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

38th of 57 rated business consultants


Job description

Job Family:

Data Science & Analysis


Travel Required:

Up to 25%


Clearance Required:

Active Secret

What You Will Do:

As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and operational processes that enable scalable, secure, and reliable deployment of machine learning solutions for federal clients. You will partner closely with data scientists, AI engineers, data engineers, and government stakeholders to operationalize models across development, testing, and production environments.

You will play a critical role in enabling secure AI and ML delivery within DoD and federal financial environments, ensuring models are repeatable, auditable, and compliant with federal standards.

Key responsibilities include:

  • Design, build, and maintain endtoend MLOps pipelines, supporting model training, testing, deployment, monitoring, and retraining

  • Implement CI/CD workflows for ML models and data pipelines in secure federal environments

  • Operationalize machine learning models built by data science teams and ensure production readiness

  • Develop and manage model versioning, artifact management, and experiment tracking

  • Implement monitoring solutions for model performance, drift, data quality, and pipeline health

  • Automate infrastructure provisioning and deployment using infrastructureascode and DevOps best practices

  • Support auditability, explainability, and governance of AI/ML systems

  • Collaborate with stakeholders to align MLOps architectures with mission needs and security requirements

What You Will Need:
  • US Citizenship required

  • An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance.

  • Bachelor's degree obtained.

  • 3-5 years of experience in MLOps, ML engineering, data engineering, DevOps, or related technical roles

  • Strong experience with Python and ML tooling supporting model packaging, deployment, and monitoring

  • Handson experience building CI/CD pipelines for data and ML workloads

  • Experience with containerization and orchestration (e.g., Docker, Kubernetes, or managed equivalents)

  • Experience working with secure cloud or hybrid environments supporting federal or DoD clients

  • Familiarity with ML lifecycle management concepts including versioning, reproducibility, and monitoring

  • Ability to work across technical and nontechnical teams and communicate complex system designs clearly

What Would Be Great to Have:
  • Experience supporting the Department of Defense, including work associated with Advana or enterprise analytics platforms

  • Bachelor's degree in computer science, Engineering, Data Science, or a related technical discipline

  • Experience operationalizing ML solutions that work with federal financial or budgetary data

  • Handson experience with Databricks, including MLflow, Spark, and Delta Lake

  • Experience deploying or maintaining ML workflows in Palantir Foundry

  • Familiarity with governance, compliance, and risk controls associated with AI in federal environments

  • Experience in Azure (including Azure Government) or AWS GovCloud

  • Knowledge of responsible AI, model risk management, or regulated ML environments

  • Master's degree in a relevant technical field

The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs.


What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

  • Medical, Rx, Dental & Vision Insurance

  • Personal and Family Sick Time & Company Paid Holidays

  • Position may be eligible for a discretionary variable incentive bonus

  • Parental Leave and Adoption Assistance

  • 401(k) Retirement Plan

  • Basic Life & Supplemental Life

  • Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts

  • Short-Term & Long-Term Disability

  • Student Loan PayDown

  • Tuition Reimbursement, Personal Development & Learning Opportunities

  • Skills Development & Certifications

  • Employee Referral Program

  • Corporate Sponsored Events & Community Outreach

  • Emergency Back-Up Childcare Program

  • Mobility Stipend

About Guidehouse

Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.

If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.

All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.

If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties.

Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.


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