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Product Manager Machine Learning Jobs in Oregon (NOW HIRING)

Upstart

Senior Manager, Machine Learning

OR · Remote

The Team Our Core ML organization is looking for an exceptional, hands-on Machine Learning Manager ... Take ownership of a specific product area (like Cash Line or Auto) and serve as the de facto ML ...

Instacart

OR · On-site

You will help design and build end-to-end machine learning solutions. * You will be working in ... You will work closely with engineers, product managers, other teams, and both internal and external ...

HealthEdge

Machine Learning Engineer

Work directly with product managers, implementation consultants, engineers, and business operations teams to identify pain points, scope solutions, and iterate toward measurable outcomes. You are the ...

Chabez Tech

Machine Learning Engineer

Portland, OR

Job Title: Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview ... in production systems • Strong problem-solving skills and ability to work with complex, real ...

Chabez Tech

Machine Learning Engineer

Portland, OR · On-site

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 ... in production systems • Strong problem-solving skills and ability to work with complex, real ...

Chabez Tech

Machine Learning Engineer

Portland, OR

Job Title: Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview ... production systems Strong problem-solving skills and ability to work with complex, real-world ...

Instacart

OR · On-site

We build rich product and knowledge graphs from catalog data imported from hundreds of retailers ... Working on graph data management and knowledge discovery over one of the world's largest grocery ...

Netflix

OR

The Machine Learning & Inference Research (MLIR) team works on core methodological development in ... Work closely with a wide range of partners (scientists, engineers, designers, product managers ...

Workiva, Inc.

Staff Machine Learning Engineer

OR · On-site +1

As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and ... Collaborate with software, data architects, and product managers to design complete software ...

Netflix

OR

$523K - $920K/yr

... improve production ML services. Passionate about leading teams through ambiguous and complex ... Master's or PhD in Machine Learning, Computer Science, or a closely related field. 6+ years of ...

Zelis

Product Manager - AI

OR · On-site +1

Position Overview PRODUCT MANAGER, AI Remote Our enterprise Data and Technology team at Zelis is ... Understanding and experience with machine learning, data engineering, and software engineering.

OneStudyTeam

Senior Machine Learning Engineer

OR · On-site +1

$140K - $190K/yr

Collaborate across teams of data scientists, product managers, designers, engineers, and domain ... Strong understanding of machine learning fundamentals (model selection, training, evaluation ...

Cotiviti

The RVA Product Manager is a strong collaborator and communicator, passionate about delivering ... Develop and own product strategy and roadmaps for Artificial Intelligence (AI), Machine Learning ...

Cotiviti

As an AI Product Manager, you empathize with our lines of business and identify clear objectives to ... Participate in design sessions to continuously develop and improve the Cotiviti machine learning ...

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All 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 May 30, 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 are the key skills and qualifications needed to thrive as a Product Manager, Machine Learning, and why are they important?

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 specializing in 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 does a Product Manager for 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 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 May 2026, with employment types broken down into 2% As Needed, 59% Full Time, 35% Part Time, and 4% Contract. Highlights an 93% Physical, and 7% Remote job distribution, with an average salary of $168,536 per year, or $81 per hour.
Senior Manager, Machine Learning

Senior Manager, Machine Learning

Upstart

Remote

Other

Posted 24 days ago

Job description

The Team 

Our Core ML organization is looking for an exceptional, hands-on Machine Learning Manager to join our leadership group. Because our ML teams share common codebases and modeling pipelines, we are searching for generalist ML leaders who can be deployed to the areas of our business where they will have the most impact.

Rather than hiring for one specific silo, we match candidates to the right team based on their unique background, technical strengths, and interests. Depending on your expertise, you could step in to lead one of several high-priority teams, such as:

  • Cash Line: Leading the 01 ML innovation for our brand new subscription-based line of credit, building core underwriting and customer behavior models (churn, draw, default) in a domain with limited data and long feedback loops.
  • Auto Retail Lending (ARL): Tackling unique, deep-modeling challenges such as competing risk, collateral, and recovery modeling for dealership-based auto lending.
  • Underwriting: Managing MLE-heavy engineering and research efforts to optimize our core unsecured personal loan models.

This is a highly technical player-coach role. You will not be managing a massive organization; instead, you will lead a small, nimble team of individual contributors (Research Scientists, Data Scientists, or Machine Learning Engineers). This role is designed for a builder who wants to retain meaningful strategic scope, maintain a roughly 50/50 split between technical execution and management, and act as the definitive ML owner for their product space.

How you'll make an impact:

  • Act as a Player-Coach: Dive deep into the data and code. You will spend a significant portion of your time making direct technical contributions, reviewing code/PRs, and understanding the mathematical nuances of your team's models.
  • Lead Strategic Initiatives: Take ownership of a specific product area (like Cash Line or Auto) and serve as the de facto ML leader in cross-functional strategy meetings.
  • Drive 01 and Scaling ML Efforts: Depending on your team placement, you may build out entirely new capabilities from scratch or optimize highly mature models dealing with massive scale and shifting macro-economic regimes.
  • Translate Models to Business Impact: Design and refine decision engines that translate model predictions into accurate, transparent, and customer-friendly lending outcomes.

What we're looking for:

  • Minimum Qualifications
    • Experience
      • 6+ years of experience developing and deploying machine learning models in production with direct business impact.
      • Proven track record of leading high-impact ML initiatives from research through productionization.
      • Advanced degree in a quantitative field (e.g., computer science, statistics, economics, operations research, etc).
    • Technical abilities and attitude
      • Strong technical judgment and ability to dive deep into model design, data analysis, and evaluation. 
      • Keen statistical, economic and business intuition, and comfort with reasoning under uncertainty and data limitations.
      • Knowledge of production ML, ability to adapt to new tech stacks and get in the weeds of work output from the team. 
      • Excited and able to make direct technical contributions when needed.
    • Leadership
      • Exceptional leadership skills with experience developing teams of highly technical ML scientists.
      • Attract, mentor, and grow a top-tier team of ML scientists passionate about expanding access to credit.
      • Proven ability to influence and collaborate cross-functionally with Product, Engineering, Capital Markets and other teams.
      • Strong project management skills with experience scaling processes and operational workflows.
  • Preferred Qualifications
    • PhD in Computer Science, Statistics, Economics or a related field.
    • Proven success building and scaling new ML products from inception.
    • Familiarity with lending, lines of credit, or other consumer finance products. 
    • Hands-on familiarity with end-to-end ML infrastructure, including experimentation pipelines, feature stores, and model monitoring. Ability to uplevel team's engineering practices and drive cross-functional engineering design.

Position Location - This role is available in the following locations: US Remote

Time Zone Requirements - This team operates on the East/West Coast time zones.

Travel Requirements - This team has regular on-site collaboration sessions. These occur 3-4 days per quarter at one of our offices. If you need to travel to make these meetups, Upstart will cover all travel related expenses.

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