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Product Manager Machine Learning Jobs (NOW HIRING)

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 · 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 · 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 ...

Overstory

Engineering Manager, Machine Learning

Our product teams are cross functional and will typically include product managers, designers ... Enable our Machine Learning and data teams to operate as highly productive, cross-functional teams ...

Twilio

Senior Manager, Machine Learning

Partner with Product Managers and Architects to distill customer needs into actionable technical ... in machine learning /data engineering. 5+ years of experience leading and managing engineering ...

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 ...

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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 Jul 9, 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 is the AI PM salary?

The salary for a Product Manager specializing in Machine Learning typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, often including bonuses and stock options. Strong knowledge of AI tools and data-driven decision-making are common requirements for this role.

What is a $900000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers or AI research directors, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with significant experience and leadership responsibilities.

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 machine learning product manager do?

A machine learning product manager oversees the development and deployment of AI and machine learning products, coordinating between data scientists, engineers, and stakeholders. They define product requirements, prioritize features, and ensure that machine learning models meet business goals and performance standards, often using tools like data analysis and model monitoring platforms.

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.

Which 3 jobs will survive AI?

Product Managers in machine learning will continue to be essential as they oversee AI projects, coordinate teams, and ensure alignment with business goals. Roles requiring complex problem-solving, creativity, and human judgment—such as data scientists and AI ethics specialists—are also likely to persist. These jobs demand skills that are difficult for AI to fully replicate, including strategic thinking and interpersonal communication.

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, 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.
More about Product Manager Machine Learning jobs
What cities are hiring for Product Manager Machine Learning jobs? Cities with the most Product Manager Machine Learning job openings:
What states have the most Product Manager Machine Learning jobs? States with the most job openings for Product Manager Machine Learning jobs include:
What job categories do people searching Product Manager Machine Learning jobs look for? The top searched job categories for Product Manager Machine Learning jobs are:
Product Manager Machine Learning jobs near you
Infographic showing various Product Manager Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.
Machine Learning Manager

Machine Learning Manager

Hive

San Francisco, CA • On-site

$180K - $250K/yr

Full-time

Posted 7 days ago

Job description

About Hive 

Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!

Machine Learning Manager

In order to execute our vision, we're constantly growing our machine learning team.  We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential.  We value hard workers who have no qualms working with terabyte-scale datasets. We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
  • Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
  • Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
  • Participate in products technical design and architecture
  • Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
  • Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
  • Implement and manage security protocols such as training, code review, and best practices
  • Own and manage the risk and security of your business function in coordination with the Security Team
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
  • Undergraduate or graduate degree in computer science or similar technical field
  • 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
  • Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
  • 2+ years experience managing machine learning teams
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
  • Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
  • Have experience collaborating with product managers and labeling team in delivering model improvements
Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Hive and we hope to meet you soon!

The current expected base salary for this position ranges from $180,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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