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Product Manager Machine Learning Jobs in Oregon (NOW HIRING)

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

... production. In this role, you will lead engineering initiatives that turn high-impact modeling ... This includes building a unified embeddings platform for training, serving, and managing ...

$139K - $168K/yr

To do so, we have two knowledge sharing products: * Quora : a global knowledge sharing platform ... At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ...

$139K - $168K/yr

To do so, we have two knowledge sharing products: * Quora : a global knowledge sharing platform ... At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ...

$139K - $168K/yr

To do so, we have two knowledge sharing products: * Quora : a global knowledge sharing platform ... At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ...

$139K - $168K/yr

To do so, we have two knowledge sharing products: * Quora : a global knowledge sharing platform ... At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ...

To do so, we build Machine Learning technology that can accurately predict which apps a user will ... Our technology is innovative and we have solid product-market fit; as a result, we've already ...

Sr. Product Manager

$126K - $166K/yr

Artificial Intelligence and Machine Learning exposure, training, and use is a plus. * Previous remote product management experience preferred. * Strong writer and clear communicator, with excellent ...

OR · On-site

Define deployment approaches and production infrastructure for AI/ML models and applications ... You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a ...

OR

$170K - $334K/yr

Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform including newsfeed, notifications, ads relevance ...

OR

$205K - $355K/yr

Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform, including newsfeed, notifications, ad relevance ...

Showing results 41-60

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 Aug 8, 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.

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 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 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 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.
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 cities in Oregon are hiring for Product Manager Machine Learning jobs? Cities in Oregon with the most Product Manager Machine Learning job openings:
Infographic showing various Product Manager Machine Learning job openings in Oregon as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $168,536 per year, or $81 per hour.

Full-time

Re-posted 22 days ago


Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination