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Mlops Data Engineer Jobs in Oregon (NOW HIRING)

MLOps and CI/CD automation * Cloud infrastructure and DevOps * Data lifecycle management * Risk and dependency management * Resource planning and forecasting * Executive reporting and stakeholder ...

$147K - $211K/yr

Account for any GCP implementation with MLOps and Agentic AI tools in Vertex AI * Enhance ... GCP Professional certifications (Cloud Architect, DevOps Engineer, or Data Engineer). * Experience ...

Senior Machine Learning Engineer

OR · Remote

$140K - $190K/yr

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in ... Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy ...

Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field. * 3+ years of experience in machine learning engineering, with particular emphasis on MLOps, model ...

OR · On-site

$104K - $143K/yr

Due to the sensitive nature of our engineering work, Anno.ai enforces strict digital footprint and ... data integrity, traceability, and operational reliability * Evaluate and integrate emerging MLOps ...

Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field. * 3+ years of experience in machine learning engineering, with particular emphasis on MLOps, model ...

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 ...

$55.75 - $74.50/hr

Partner with Data & AI teams to operationalize AI workloads safely and compliantly within Google Cloud environments. DevOps, Automation & MLOps Foundations * Build secure CI/CD pipelines for ...

Senior Backend Software Engineer, ObservoAI

OR · Remote

$122K - $161K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Drive the development and optimization of ML-driven data routing and transformation engines to ... and MLOps practices for production ML systems. * Expert knowledge of observability tools and ...

AI Engineer, Sr

Newberg, OR

$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

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

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Required : • Bachelor's degree in computer science, engineering, data science, mathematics, or a ... with MLOps practices including model monitoring, versioning, and lifecycle management • ...

OR · On-site

  • Dental

  • Vision

  • Retirement

  • PTO

You will collaborate closely with clients, Sales, data scientists, ML engineers, data engineers ... with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow for enterprise-scale ML.

Showing results 21-40

Mlops Data Engineer information

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 machine learning models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

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 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 is the salary of MLOps Data Engineer?

The salary of an MLOps Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and company size. Professionals with advanced skills in cloud platforms, automation, and machine learning tools may earn higher compensation.
What are popular job titles related to Mlops Data Engineer jobs in Oregon? For Mlops Data Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Mlops Data Engineer jobs in Oregon look for? The top searched job categories for Mlops Data Engineer jobs in Oregon are:
What cities in Oregon are hiring for Mlops Data Engineer jobs? Cities in Oregon with the most Mlops Data Engineer job openings:

Program Manager - AI Pipeline Management

Aptive

On-site

Full-time

Re-posted 17 days ago


Aptive Environmental rating

5.6

Company rating: 5.6 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

30th of 35 rated pest control companies


Job description

Job Summary

We are seeking a highly organized and technically savvy Program Manager with expertise in AI pipeline management to support Department of Veterans Affairs (VA) initiatives focused on AI/ML operations, healthcare analytics, automation, and scalable digital transformation. This role will oversee the planning, coordination, execution, and optimization of AI development pipelines across data engineering, model development, deployment, governance, cybersecurity, and operational monitoring within a federal healthcare environment.

The ideal candidate combines strong program management capabilities with hands-on understanding of AI workflows, MLOps, cloud infrastructure, federal compliance requirements, and enterprise-scale healthcare technology delivery practices. The Program Manager will work closely with VA stakeholders, clinical and business teams, engineers, architects, and federal leadership to ensure successful delivery of secure, compliant, and mission-driven AI solutions that improve Veteran outcomes and operational efficiency.

Primary Responsibilities

Program & Portfolio Management

  • Lead enterprise AI initiatives from planning through deployment and operationalization.
  • Manage timelines, budgets, dependencies, risks, and stakeholder communications across multiple AI programs.
  • Coordinate cross-functional teams including data scientists, ML engineers, software engineers, cloud architects, security, and business stakeholders.
  • Establish program governance frameworks, KPIs, and reporting structures.

AI Pipeline Management

  • Design, optimize, and oversee AI/ML lifecycle pipelines including:
    • Data ingestion and preprocessing
    • Model training and validation
    • CI/CD for ML models
    • Model deployment and monitoring
    • Retraining and performance management
  • Collaborate with engineering teams to improve automation, scalability, and reliability of AI workflows.
  • Ensure integration of AI systems with enterprise platforms and business applications.
  • Drive implementation of MLOps best practices and standardized delivery frameworks.

Operational Excellence

  • Monitor AI pipeline performance, SLAs, and operational metrics.
  • Identify bottlenecks and implement process improvements.
  • Ensure compliance with security, privacy, governance, and responsible AI standards.
  • Support incident management and root cause analysis related to AI systems.

Stakeholder Engagement

  • Translate technical AI concepts into business-focused updates and recommendations.
  • Facilitate executive-level reporting and strategic planning.
  • Align AI program objectives with organizational goals and digital transformation initiatives.
Minimum Qualifications
  • Master's degree in Computer Science, Engineering, Information Systems, Business, or related field.
  • PMP, PgMP, Scrum Master, SAFe, or Agile certification.
  • 5+ years of program or project management experience.
  • 3+ years managing AI/ML, data engineering, or MLOps initiatives.
  • Strong understanding of AI/ML lifecycle management and cloud-based AI platforms.
  • Experience with Agile, Scrum, SAFe, or hybrid delivery methodologies.
  • Proven experience managing enterprise-scale technical programs.
  • Excellent communication, organizational, and leadership skills.
Desired Qualifications

Preferred Qualifications

  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Familiarity with tools and technologies such as:
    • MLflow
    • Airflow
    • Databricks
    • Jenkins/GitHub Actions
    • Python
    • Terraform
    • Snowflake
  • Knowledge of AI governance, model risk management, and responsible AI practices.
  • Experience in VA or other Federal Agencies

Technical Skills

  • AI/ML pipeline orchestration
  • MLOps and CI/CD automation
  • Cloud infrastructure and DevOps
  • Data lifecycle management
  • Risk and dependency management
  • Resource planning and forecasting
  • Executive reporting and stakeholder management

Soft Skills

  • Strategic thinker with strong analytical abilities
  • Strong leadership and team coordination capabilities
  • Excellent problem-solving and decision-making skills
  • Ability to manage competing priorities in fast-paced environments
  • Strong collaboration and communication skills across technical and non-technical teams
About Aptive

Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation.

We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day.

Founded: 2012Employees: 300+ nationwide

EEO Statement

Aptive is an equal opportunity employer. We consider all qualified applicants for employment without regard to race, color, national origin, religion, creed, sex, sexual orientation, gender identity, marital status, parental status, veteran status, age, disability, or any other protected class.

Veterans, members of the Reserve and National Guard, and transitioning active-duty service members are highly encouraged to apply.

Employment Type: FULL_TIME

What Aptive Environmental employees say

Pay

Benefits

Hours and flexibility

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