Product Manager (Specialized in Machine Learning)
Carter Support Services
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Atlanta, GA
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Entry level
Posted April 3, 2026
2 variants
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Responsibilities
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
Not Met Priorities
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Requirements
- 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
Preferred Skills
- 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
Product Manager (Machine Learning) Company: Carter Support Services Location: Atlanta, Georgia 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
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