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Product Manager Machine Learning Jobs in Oregon (NOW HIRING)

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... As an example, we manage catalog data imported from hundreds of retailers, and we build product and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... As an example, we manage catalog data imported from hundreds of retailers, and we build product and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... As an example, we manage catalog data imported from hundreds of retailers, and we build product and ...

New

Instacart

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... As an example, we manage catalog data imported from hundreds of retailers, and we build product and ...

New

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

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Showing results 21-40

All JobsProduct Machine Learning JobsProduct Manager Machine Learning JobsProduct Manager Machine Learning Jobs in Oregon

Product Manager Machine Learning information

See Oregon salary details

$54.5K

$168.5K

$208.3K

How much do product manager machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for product manager machine learning in Oregon is $168,536.00, according to ZipRecruiter salary data. Most workers in this role earn between $149,100.00 and $208,300.00 per year, depending on experience, location, and employer.

What does a product manager machine learning do?

A Product Manager for Machine Learning oversees the development and deployment of machine learning products or features. They work closely with data scientists, engineers, and business stakeholders to identify opportunities where machine learning can deliver value, define product requirements, and guide projects from conception to launch. Their responsibilities include setting the product vision, prioritizing features, ensuring alignment with business goals, and evaluating the impact of machine learning solutions. They also help bridge the gap between technical teams and non-technical stakeholders by translating complex concepts into actionable plans.

What are the key skills and qualifications needed to thrive as a product manager machine learning?

To thrive as a Product Manager, Machine Learning, you need a solid understanding of product lifecycle management, data analytics, and machine learning concepts—often supported by a technical degree and relevant experience. Familiarity with tools like Python, SQL, JIRA, and machine learning frameworks, as well as certifications such as PMP or Agile, is highly beneficial. Outstanding communication, stakeholder management, and problem-solving skills help you bridge the gap between technical teams and business objectives. These abilities are crucial to successfully guide ML products from ideation to launch, ensuring they deliver real value and align with organizational goals.

How does a product manager machine learning typically collaborate with data scientists and engineering teams?

Product Managers in Machine Learning work closely with both data scientists and engineering teams to translate business objectives into viable AI-driven products. They facilitate communication by defining clear requirements, prioritizing features, and ensuring that the technical roadmap aligns with user needs and company strategy. Regular meetings, progress reviews, and shared documentation are common practices to keep everyone aligned. This cross-functional collaboration is essential for addressing feasibility, optimizing models, and delivering successful products on schedule.

What is the difference between Product Manager Machine Learning vs Data Scientist?

AspectProduct Manager Machine LearningData Scientist
Primary FocusOverseeing ML product development, strategy, and deploymentAnalyzing data, building models, and deriving insights
Required SkillsProduct management, ML understanding, cross-functional collaborationStatistics, programming, data analysis
Work EnvironmentProduct teams, engineering, business stakeholdersData analysis teams, research, engineering
Common CertificationsProduct management certifications, ML coursesData science certifications, programming skills

While both roles involve machine learning, Product Manager Machine Learning focuses on guiding ML products from conception to deployment, working closely with engineering and business teams. Data Scientists primarily analyze data and develop models to extract insights. The roles complement each other but differ in their core responsibilities and skill sets.

What are popular job titles related to Product Manager Machine Learning jobs in Oregon?

For Product Manager Machine Learning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Product Manager Machine Learning jobs in Oregon look for?

The top searched job categories for Product Manager Machine Learning jobs in Oregon are:

What cities in Oregon are hiring for Product Manager Machine Learning jobs?

Cities in Oregon with the most Product Manager Machine Learning job openings:

Product Manager Machine Learning jobs near you
Infographic showing various Product Manager Machine Learning job openings in Oregon as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $168,536 per year, or $81 per hour.

Product Manager | Mandarin-speaking | Remote (Portland-based) | Competitive Salary + Benefits | Tech

White Bay

Portland, OR • On-site, Remote

Full-time

Posted 11 days ago

Job description

Product Manager | Mandarin-speaking | Remote (Portland-based) | Competitive Salary + Benefits | Tech



The Company

A high-growth technology organization operates at the intersection of advanced software, data, and digital commerce. This ambitious team is building sophisticated tools that help modern businesses scale more efficiently, combining automation with strategic human insight. With a strong emphasis on learning, accountability, and thoughtful execution, the organization values people who thrive in fast-moving environments and take ownership of meaningful outcomes.


The Role

They are seeking an AI Product Manager to design and deliver intelligent product capabilities that sit at the intersection of user needs, machine learning, and business strategy. This role owns the development of AI-powered features ranging from optimization and recommendations to reporting intelligence, automated workflows, and emerging generative experiences.

This position is well suited for someone who enjoys working hands-on with technical teams while staying deeply connected to real customer problems. The role partners closely with engineering, data science, and design to ensure AI systems deliver meaningful, trusted outcomes.


The Responsibilities


AI Product Strategy

  • Define and evolve the roadmap for AI-driven functionality, including prediction models, optimization systems, scoring frameworks, and insight-generation tools.
  • Translate complex customer challenges into machine learning opportunities, thoughtfully balancing automation with human oversight.
  • Collaborate with data science, engineering, and design to shape explainable and reliable AI behavior.


Cross-Functional Delivery

  • Work closely with engineering, data science, design, and operations teams to bring AI products from concept to production.
  • Align business partners, go-to-market teams, and leadership through clear priorities, metrics, and product narratives.
  • Lead discussions around feasibility, including data readiness, algorithmic tradeoffs, and performance constraints.


Model and Data Lifecycle

  • Partner with data science to define data needs, training approaches, evaluation methods, and success criteria for models.
  • Design and run experiments such as A/B tests, offline evaluations, and iterative model improvements.
  • Establish feedback loops between users, models, and outcomes to drive continuous improvement.


User Experience and Adoption

  • Ensure AI features are easy to use, dependable, and transparent for both customers and internal teams.
  • Shape workflows, interfaces, and explanations that build trust in AI-driven recommendations.
  • Balance automation with appropriate configurability, safeguards, and override mechanisms.


Product Execution

  • Own product documentation including requirements, specifications, user stories, and acceptance criteria.
  • Prioritize initiatives based on customer impact, data opportunity, technical feasibility, and strategic value.
  • Track success using metrics such as accuracy, lift, ROI, adoption, latency, and user satisfaction.


The Requirements

  • Bachelor’s degree in Computer Science, Engineering, AI/ML, Business, or a related field.
  • 2–5 years of product management experience, preferably working with data- or ML-driven products.
  • Proven ability to deliver products end-to-end in technical, data-rich environments.
  • Solid understanding of machine learning concepts including model training, evaluation, prediction systems, and optimization logic.
  • Familiarity with data pipelines, feature engineering, and experimentation frameworks.
  • Experience working in Agile environments with engineering and data science teams.
  • Strong communication skills with the ability to explain complex AI concepts to non-technical audiences.
  • Analytical mindset with experience using SQL, dashboards, or data analysis tools
  • Mandarin language skills to support cross-regional collaboration.



Preferred Qualifications

  • Experience in advertising technology, marketing platforms, retail media, or demand-side systems.
  • Exposure to generative AI, large language models, agent-based workflows, or retrieval-augmented systems.
  • Experience designing explainability, trust, safety, or model governance features.


Apply Now

This role offers the chance to build practical AI products that directly influence customer outcomes at scale. If they enjoy solving complex problems, collaborating across disciplines, and shaping how AI is used responsibly in real-world systems, they are encouraged to apply and be part of what comes next.


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