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Product Manager Machine Learning Jobs in Dallas, TX

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$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 ...

Precision Technologies

Senior Product Manager

Irving, TX · On-site

$121K - $160K/yr

Senior Product Manager - AI (13582) Location: Irving, TX Duration: Contract Position Summary: We ... You will identify high-impact opportunities to apply artificial intelligence, machine learning, and ...

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

You'll work with large-scale image and video data, building and optimizing production-grade vision ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

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All JobsProduct Machine Learning JobsProduct Manager Machine Learning JobsProduct Manager Machine Learning Jobs in Dallas, TX

Product Manager Machine Learning information

See Dallas, TX salary details

$50.9K

$157.7K

$194.9K

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

As of Sep 10, 2026, the average yearly pay for product manager machine learning in Dallas, TX is $157,688.00, according to ZipRecruiter salary data. Most workers in this role earn between $139,500.00 and $194,900.00 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 Dallas, TX?

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

What job categories do people searching Product Manager Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Product Manager Machine Learning jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Product Manager Machine Learning jobs?

Cities near Dallas, TX 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 Dallas, TX as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $157,688 per year, or $75.8 per hour.

Manager, Machine Learning Engineer

Dallas, TX

Vanguard
Photography Services • 1 - 5K employees
Learn more about Vanguardexternal

$101K - $133K/yr

Full-time

Re-posted 7 days ago

Key responsibilities

  • Leads a team of Machine Learning Engineers in designing, building, deploying, and scaling AI/ML solutions.

  • Partners with cross-functional teams to deliver production-grade AI capabilities and ensure alignment with business objectives.

  • Oversees the end-to-end solution delivery, including architecture planning, implementation, deployment, monitoring, and continuous improvement.

Job description

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners closely with Product, Data Science, Architecture, and Technology teams to deliver production-grade AI capabilities with a strong focus on scalability, reliability, governance, and operational excellence. Drives end-to-end solution delivery from architecture planning through implementation, deployment, monitoring, and continuous improvement

Core Responsibilities

  • Provides leadership in hiring, coaching, talent development, performance management, and compensation decisions in accordance with Human Resources policies and procedures.

  • Partners with Enterprise, Solution, and Domain Architects to define AI/ML solution architectures and translate strategic initiatives into executable roadmaps, epics, and engineering workstreams.

  • Leads cross-functional delivery across Product, Data Science, Platform, and Engineering teams, driving solutions from concept through production while ensuring alignment to business objectives and enterprise standards.

  • Establishes engineering practices, reusable frameworks, and platform capabilities that improve scalability, consistency, and delivery efficiency across AI/ML initiatives.

  • Oversees the design, implementation, and evolution of data, feature, and model pipelines to support reliable and scalable AI/ML solutions.

  • Applies expertise in machine learning, statistics, optimization, and experimentation methodologies to operationalize predictive and decision-support capabilities.

  • Evaluates data quality, feature readiness, and model inputs in partnership with Data Science teams to support successful model development and deployment.

  • Drives operational excellence through automation, observability, monitoring, incident management, and continuous improvement practices for production AI/ML systems.

  • Ensures adherence to enterprise governance, security, risk, compliance, and model lifecycle management requirements.

  • Engages business and technology stakeholders to understand objectives, assess opportunities, and translate complex requirements into actionable technical solutions.

  • Supports departmental planning, prioritization, and execution of strategic objectives while balancing delivery commitments, operational needs, and organizational goals.

  • Establishes scalable operating models, support processes, and service standards that enable long-term sustainability of AI/ML products and platforms.

  • Communicates technical strategy, solution recommendations, delivery progress, and business impact to senior technology and business leaders.

  • Participates in special projects and performs other duties as assigned.

Qualifications

  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

  • Minimum of eight years related work experience.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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