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Product Manager Machine Learning Jobs in Georgia

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162K - $342K/yr

We integrate industry-leading solutions-including Unified Endpoint Management,Virtual Appsand ... You'llwork closely with engineering and product teams to operationalize models across ...

Leverage Azure Container Registry to securely manage container images and deploy scalable workloads ... production. Ensure comprehensive logging and observability for containerized model endpoints ...

New

Showing results 41-60

Product Manager Machine Learning information

See Georgia salary details

$43.5K

$134.6K

$166.3K

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

As of Aug 10, 2026, the average yearly pay for product manager machine learning in Georgia is $134,599.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $166,300.00 per year, depending on experience, location, and employer.

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 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 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?

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.
What are popular job titles related to Product Manager Machine Learning jobs in Georgia? For Product Manager Machine Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Product Manager Machine Learning jobs in Georgia look for? The top searched job categories for Product Manager Machine Learning jobs in Georgia are:
What cities in Georgia are hiring for Product Manager Machine Learning jobs? Cities in Georgia with the most Product Manager Machine Learning job openings:
Infographic showing various Product Manager Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $134,599 per year, or $64.7 per hour.

Machine Learning Lead Engineer

Cox Communications, Inc.

Atlanta, GA • On-site, Remote

$134K - $224K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago


Cox Communications rating

8.3

Company rating: 8.3 out of 10

Based on 127 frontline employees who took The Breakroom Quiz

18th of 97 rated telecommunications companies


Job description

Company

Cox Automotive - USA

Job Family Group

Data Intelligence & Science

Job Profile

Machine Learning Lead Engineer

Management Level

Manager - Non People Leader

Flexible Work Option 

Hybrid - Ability to work remotely part of the week

Travel %

Yes, 15% of the time

Work Shift

Day

Compensation

Compensation includes a base salary in the range of $134,900.00 - $224,900.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.

Job Description

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting-edge research with the responsibility of building a culture of continuous learning and knowledge sharing. You'll lead efforts to identify, evaluate, and prototype emerging ML technologies while establishing our company as a thought leader in the ML community. Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and improve data quality. Structures, trains, and deploys models to learn from complex data across multiple modalities (e.g., structured, unstructured, image, video, audio) to uncover patterns and develop practical solutions. Possesses deep knowledge in at least one sub-area of machine learning, such as deep learning, generative AI, computer vision, optimization, predictive models, or causal machine learning.

WHAT YOU'LL DO

Key Responsibilities

  • Accelerate ML development using AI tools for code generation, feature engineering, optimization, and validation
  • Stay up to date with advancements in ML, AI, and emerging technologies
  • Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference
  • Optimize model performance, scalability, and reliability in production environments
  • Collaborate cross-functionally to translate model insights into business value and communicate project updates
  • Contribute to ML infrastructure improvements, best practices, and documentation
  • Partner with engineering teams to integrate AI-enhanced models and establish automated monitoring frameworks.
  • Establish AI governance practices including bias detection, interpretability, compliance monitoring, and responsible deployment.
  • Mentor teams in AI adoption, share best practices, and promote responsible AI innovation culture.
  • Lead AI transformation initiatives including tool evaluation, governance development, and strategic adoption planning.
  • Analyzes complex data sets to solve real-world business and customer use cases.
  • Performs end-to-end development of machine learning models
  • May assist with or lead the development of industry whitepapers or other technical publications.
  • Continuously evaluate AI processes for accuracy, efficiency, and business impact while staying current on emerging technologies.
  • Design agentic workflows for autonomous training, data pipelines, and analytical problem solving appropriate to experience level.

Key AI Use Cases

  • AI-Accelerated Model Development:Use GitHub Copilot, Claude Code for rapid ML prototyping, automated feature engineering, and intelligent hyperparameter optimization.
  • Agentic ML Workflows:Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training pipelines, multi-step analysis, and collaborative research.
  • AI-Enhanced Model Interpretation:Build on traditional frameworks (SHAP, LIME) with AI tools for enhanced stakeholder communication and automated insights.
  • AI-Powered Research:Leverage manual/autonomous competitive intelligence and research acceleration tools for methodology discovery and algorithm innovation.

WHO YOU ARE

Required Skills

  • Proficiency in AI development tools (GitHub Copilot, Claude, GPT-4) for ML development with ability to validate AI outputs for production readiness.
  • Understanding of agentic frameworks (AWS AgentSquad, AWS Strands, LangChain, agent patterns) with progression from basic configuration to custom enterprise system design.
  • Knowledge of AI ethics, responsible AI practices, and governance frameworks for business-critical ML deployment.
  • Ability to leverage AI like Co-Pilot for technical communication to stakeholders and cross-functional collaboration.
  • Commitment to continuous learning in AI-augmented data science and responsible AI use.

Required Qualifications

  • Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future.
  • Bachelor's degree in a related discipline and 6 years' experience in Machine Learning; or a different combination, such as a master's degree and 4 years' experience; a Ph.D. and 1 years' experience in a related field; or 18 years' experience in a related field with no degree
  • Minimum of 6 years of experience as a Machine Learning Engineer or equivalent
  • Deep expertise in multiple ML domains and familiarity with emerging research areas
  • Strong experience in technology evaluation, competitive analysis, and strategic planning
  • Comfortability with non-deterministic systems
  • Product background- understand how to prioritize, collaborate across teams, manage dependencies with others, set strategy
  • Experience in Rally, Jira or similar tools
  • Skilled in analytical thinking, consulting, requirements analysis, system and technology integration and technology savvy.
  • Skilled in collaborating with intent, communicating with impact, developing trust, driving innovation and striving for excellence.
  • Proven track record of leading innovative projects from concept to proof-of-concept
  • Demonstrated success in knowledge sharing and thought leadership (publications, speaking, etc.)
  • Experience building and leading high-performing research or innovation teams
  • Excellent communication skills for technical and executive audiences
  • Strong network within the ML research community
  • Experience with research collaboration and partnership development
  • Other duties as needed or required
  • Must be comfortable with change and an evolving environment

Preferred Qualifications

  • Experience in corporate research labs, innovation teams, or technology consulting
  • Track record of identifying and successfully implementing breakthrough technologies
  • Background in technology transfer from research to business applications
  • Strong presence in the ML community (conference speaking, open-source contributions, etc.)
  • Knowledge of emerging areas such as LLMs, Agents, foundation models, multimodal AI, or quantum ML

Leadership Expectations

  • Foster a culture of experimentation, learning, and calculated risk-taking
  • Drive consensus on research priorities while maintaining innovation velocity
  • Develop talent through mentoring in both technical skills and research methodologies
  • Communicate complex experimental results and strategic implications to all organizational levels
  • Lead by example in intellectual curiosity, scientific rigor, and knowledge sharing
  • Build bridges between cutting-edge research and practical business applications
  • Establish the team as a recognized center of excellence in experimental ML

Drug Testing

To be employed in this role, you'll need to clear a pre-employment drug test. Cox Automotive does not currently administer a pre-employment drug test for marijuana for this position. However, we are a drug-free workplace, so the possession, use or being under the influence of drugs illegal under federal or state law during work hours, on company property and/or in company vehicles is prohibited.

Benefits

The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.

About Us

Through groundbreaking technology and a commitment to stellar experiences for drivers and dealers alike, Cox Automotive employees are transforming the way the world buys, owns, sells - or simply uses - cars. Cox Automotive employees get to work on iconic consumer brands like Autotrader and Kelley Blue Book and industry-leading dealer-facing companies like vAuto and Manheim, all while enjoying the people-centered atmosphere that is central to our life at Cox. Benefits of working at Cox may include health care insurance (medical, dental, vision), retirement planning (401(k)), and paid days off (sick leave, parental leave, flexible vacation/wellness days, and/or PTO). For more details on what benefits you may be offered, visit our benefits page. Cox is an Equal Employment Opportunity employer - All qualified applicants/employees will receive consideration for employment without regard to that individual's age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. Cox provides reasonable accommodations when requested by a qualified applicant or employee with disability, unless such accommodations would cause an undue hardship.EOE, including disability/vets




What Cox Communications employees say

Pay

Benefits

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About Cox Communications

Sourced by ZipRecruiter

Cox Communications is the largest private telecom company in America, serving six million homes and businesses. That's a lot, but we also proudly serve our employees. Our benefits and our award-winning culture are just two of the things that make Cox a coveted place to work. If you're interested in bringing people closer through broadband, smart home tech and more, join Cox Communications today! Cox empowers employees to build a better future and has been doing so for over 120 years. With exciting investments and innovations across transportation, communications, cleantech and healthcare, our family of businesses - which includes Cox Automotive and Cox Communications - is forging a better future for us all. Ready to make your mark?

Industry

Media and telecom

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US