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Product Manager Machine Learning Jobs in Texas (NOW HIRING)

Vanguard

Manager, Machine Learning Engineer

Dallas, TX · On-site

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... Partners closely with Product, Data Science, Architecture, and Technology teams to deliver ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... production-level machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability ...

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All JobsProduct Machine Learning JobsProduct Manager Machine Learning JobsProduct Manager Machine Learning Jobs in Texas

Product Manager Machine Learning information

See Texas salary details

$48K

$148.5K

$183.5K

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

As of Aug 29, 2026, the average yearly pay for product manager machine learning in Texas is $148,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,400.00 and $183,500.00 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 Texas?

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

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

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

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

Cities in Texas 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 Texas as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, 2% Contract, and 1% Nights. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $148,510 per year, or $71.4 per hour.

Product Manager (Specialized in Machine Learning)

Houston, TX • On-site

Carter Support Services
See more jobs at Carter Support Servicesexternal

Part-time

Re-posted 13 days ago

Job description

Product Manager (Machine Learning)
Company: Carter Support Services
Location: Houston
Position Summary
We are seeking a Product Manager with deep experience in machine learning-driven products to lead the strategy, development, and lifecycle of ML-powered solutions. This role sits at the intersection of business, data science, engineering, and user experience, translating complex machine learning capabilities into scalable, valuable, and user-friendly products.
The ideal candidate understands both product management fundamentals and machine learning concepts, and can effectively guide teams through experimentation, model iteration, and production deployment while keeping a strong focus on customer outcomes and business impact.
Key Responsibilities
  • Define product vision, strategy, and roadmap for machine learning-based products
  • Translate business problems into ML product requirements and measurable success metrics
  • Partner closely with data science and engineering teams to guide model development, training, evaluation, and deployment
  • Own product discovery, including user research, hypothesis testing, and experimentation
  • Define and prioritize features using data, experimentation results, and business impact
  • Establish KPIs for ML products, including model performance, business outcomes, and user adoption
  • Manage product lifecycle from concept through launch, iteration, and scale
  • Communicate product strategy and progress to stakeholders and executive leadership
  • Ensure responsible AI practices, including fairness, transparency, and compliance considerations
Required Qualifications
  • 4+ years of product management experience, with at least 2 years working on machine learning or data-driven products
  • Strong understanding of machine learning concepts (e.g., supervised vs. unsupervised learning, model evaluation, training pipelines)
  • Experience working with data scientists, ML engineers, and software engineers
  • Ability to translate technical concepts into clear product requirements and user value
  • Experience defining success metrics and using data to drive product decisions
  • Excellent communication, stakeholder management, and prioritization skills
Preferred Qualifications
  • Experience launching ML products into production at scale
  • Familiarity with MLOps practices and model lifecycle management
  • Experience with cloud-based ML platforms (AWS, GCP, Azure)
  • Background in AI-driven products such as recommendations, forecasting, NLP, or computer vision
  • Knowledge of regulatory, ethical, and responsible AI considerations
Core Competencies
  • Strategic thinking with strong execution focus
  • Data-driven decision making
  • Customer-centric mindset
  • Ability to manage ambiguity and complex problem spaces
  • Strong cross-functional leadership
Why Join Us
  • Build innovative products powered by cutting-edge machine learning
  • Work closely with talented data science and engineering teams
  • High ownership and visibility across the organization
  • Competitive compensation, benefits, and growth opportunities

Apply