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Mlops Data Engineer Jobs in Oregon (NOW HIRING)

CookUnity

OR · On-site

  • Medical

  • Vision

  • Retirement

  • PTO

This is a hands-on role embedded with Product, CRM, Marketing, and Engineering. Responsibilities ... Production & MLOps: Own the full model lifecycle and ship models into the systems where they act ...

phData

OR · On-site

  • Dental

  • Vision

  • Retirement

  • PTO

Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, and playbooks focused on AI/ML and MLOps. * Mentor and guide ML engineers, data scientists ...

iHerb

OR · On-site

The Principal Engineer operates at the intersection of deep technical execution and broad ... using data. * MLOps experience: model deployment, monitoring, lifecycle management, and cost ...

iHerb

OR · On-site

$122K - $161K/yr

... data. * Use AI-driven SDLC tooling such as Claude Code as a daily practice for both AI and non-AI ... Exposure to MLOps tooling or model deployment pipelines. * Contributions to internal developer ...

Munich Re

Technical Architect - Data, Analytics & AI

Eugene, OR · Hybrid

$64 - $82.25/hr

  • Medical

  • Life

  • Retirement

  • PTO

... 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 ...

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 ...

Munich Re

Technical Architect - Data, Analytics & AI

Bend, OR · Hybrid

$67.50 - $87/hr

  • Medical

  • Life

  • Retirement

  • PTO

... 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 ...

Munich Re

Technical Architect - Data, Analytics & AI

Gresham, OR · Hybrid

$67.25 - $86.50/hr

  • Medical

  • Life

  • Retirement

  • PTO

... 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 ...

Munich Re

Technical Architect - Data, Analytics & AI

Hillsboro, OR · Hybrid

$66.25 - $85.25/hr

  • Medical

  • Life

  • Retirement

  • PTO

... 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 ...

Fisher Investments

Enterprise Architect - Data, AI

Portland, OR · Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Partner with product, engineering, data, and AI teams to ensure data supports reporting, analytics ... Knowledge of Machine Learning Operations (MLOps) workflows and tools for deploying, managing, and ...

Fisher Investments

Enterprise Architect - Data, AI

Gresham, OR · Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Partner with product, engineering, data, and AI teams to ensure data supports reporting, analytics ... Knowledge of Machine Learning Operations (MLOps) workflows and tools for deploying, managing, and ...

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 ...

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Showing results 41-60

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Oregon

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:
Mlops Data Engineer jobs near you

Senior Data Scientist, Retention & Product

CookUnity

OR • On-site

Full-time

Medical, Vision, Retirement, PTO

Re-posted 20 days ago

Job description

The role:

We're hiring an ML-focused Data Scientist to own retention and churn for CookUnity. In a weekly subscription business, retention is the engine of growth - the gap between a healthy customer and a churned one is often just a few weeks of activity. Your job is to predict who's at risk, understand why they leave, and power the interventions that keep customers ordering and win back the ones who go. This is a hands-on role embedded with Product, CRM, Marketing, and Engineering.

Responsibilities:
  • Churn & retention modeling: Build churn/survival models and lifecycle-state models that flag at-risk customers early and anticipate where each customer is heading.
  • Intervention & reason understanding: Power the retention interventions that act on that risk - save flows, skip/pause deflection, lifecycle messaging - and classify why customers churn so the response fits the reason rather than being generic.
  • Resurrection & win-back: Develop propensity models and personalized experiences that bring churned customers back.
  • Personalization & Next-Best-Action: Decide the right action, offer, and message per customer across product surfaces, with an uplift layer measuring incremental impact.
  • Offer & promo optimization: Determine who gets an incentive, when, and at what value - maximizing retained revenue without over-discounting.
  • Production & MLOps: Own the full model lifecycle and ship models into the systems where they act; handle monitoring, retraining, and drift.
  • Experimentation & incrementality: Design experiments and uplift measurement so we intervene on movable customers and not on those who'd retain anyway.
Qualifications:
  • 5-8+ years in data science, applied ML, or statistics, shipping production models.
  • Retention/churn depth: churn prediction, survival / time-to-event modeling, and lifecycle-state models in a subscription or recurring-revenue context.
  • Causal & experimentation rigor: uplift/incrementality measurement and A/B testing, with the judgment to separate true impact from selection effects.
  • End-to-end ML & MLOps: building, validating, and deploying models in production (CI/CD, registries, containerization, orchestration, monitoring).
  • Engineering & tooling: strong Python (pandas, scikit-learn, gradient boosting; deep learning a plus), SQL, code hygiene and reproducibility.
  • Collaboration: excellent communication; able to embed with Product/CRM/Marketing and turn models into decisions.
  • Education: BS in a quantitative field required; MS/PhD preferred.
  • Ability to leverage generative AI to increase output quality and speed.
Preferred requirements:
  • Subscription marketplaces, food-tech, or consumer marketplaces with a retention mandate.
  • Lifecycle-state / Hidden Markov models for churn.
  • Causal and uplift libraries (e.g. EconML) or survival-modeling packages.
  • Recommenders, embeddings, or personalization for retention and win-back.
Learn More About CookUnity

We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles - The values and behaviors that guide how we operate, collaborate, and scale.

We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect!

Benefits

  Health Insurance coverage

 401k Plan

 Unlimited PTO

 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

 Paid Family leave

 Compassionate Leave: 3-5 days each time the need arises

 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.

 Wellness perks: access to fitness subsidies to build a healthy lifestyle

 Personalized Spanish coach

 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

Apply