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Product Manager Machine Learning Jobs (NOW HIRING)

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Interface closely with product management, engineering, devops, labeling, and sales teams to build ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Interface closely with product management, engineering, devops, labeling, and sales teams to build ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Interface closely with product management, engineering, devops, labeling, and sales teams to build ...

Hive

Machine Learning Manager

Seattle, WA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Interface closely with product management, engineering, devops, labeling, and sales teams to build ...

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Product Manager Machine Learning information

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$51.5K

$159.4K

$197K

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

As of Sep 11, 2026, the average yearly pay for product manager machine learning in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 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.

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

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

Product Manager Machine Learning jobs near you
Infographic showing various Product Manager Machine Learning job openings in the United States as of September 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.

Manager, Machine Learning Engineering

Bellevue, WA • On-site

Warner Bros. Discovery
Media and Telecom • 10K+ employees
Learn more about Warner Bros. Discoveryexternal

Full-time

Re-posted 16 days ago

Warner Bros. Discovery rating

7.7

Company rating: 7.7 out of 10

Based on 55 frontline employees who took The Breakroom Quiz

Job description

Job Summary:
Warner Bros. Discovery is a leading entertainment company known for its iconic content and beloved brands. They are seeking a Manager of Machine Learning Engineering to lead a team focused on building next-generation AI systems for video, integrating machine learning into real-world applications to enhance creative workflows and content understanding.
Responsibilities:
• Lead a team of machine learning engineers working on video AI across understanding and creative applications
• Stay hands-on, contributing directly to modeling, prototyping, and production systems
• Drive execution across the full ML lifecycle: problem definition, modeling, evaluation, and deployment
• Partner with product, creative, and engineering teams to define priorities and deliver impactful ML-powered features
• Build and scale production-grade ML systems for video understanding and creative workflows
• Balance rapid iteration with building robust, scalable systems
• Provide technical leadership and mentorship, raising the bar for ML and engineering practices
• Collaborate with platform and infrastructure teams to ensure reliable and scalable solutions
Qualifications:
Required:
• 8+ years of experience in machine learning / software engineering, with a focus on computer vision, video understanding, and gen AI
• 2+ years of experience leading or mentoring engineers, with a strong preference for hands-on leadership
• Strong experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
• Proven track record of building and deploying end-to-end ML systems in production
• Strong background in computer vision, video understanding, or multimodal systems
• Experience with large-scale datasets and distributed systems
• Experience with generative AI techniques (e.g., diffusion, image/video generation)
• Strong system design and architecture skills
• Ability to operate in ambiguous, fast-moving environments while maintaining execution focus
• Strong collaboration and communication skills across technical, product, and creative teams
Company:
Warner Bros. Founded in 1985, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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