Machine Learning Jobs in Atlanta, GA
Machine learning jobs in Atlanta are concentrated in Midtown, Buckhead, and the tech corridor around Peachtree Street, with strong demand across fintech, healthcare technology, and enterprise software. Employers hiring right now include The Home Depot, The Coca-Cola Company, and Worldpay. See the openings below and apply to the ones that match your experience.
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Showing 5 of 20+ Machine Learning jobs
The Senior Manager, Software Engineer, Data Platform & Segmentation is a senior individual contributor accountable for the technical vision, design, and evolution of data platforms and segmentation capabilities that power Customer and Commercial product teams operating under a modern Product Operating Model.
This role functions as a hands-on technical leader and multiplier, shaping how customer, commercial, and behavioral data is modeled, segmented, and activated across products, enabling better decisions, personalization, and measurable business outcomes.
The role emphasizes deep technical expertise, product partnership, and architectural leadership, rather than people management.
Core Accountabilities
Product Model & Discovery Partnership
- Partner closely with Product Managers, Designers, and Tech Leads to co-own outcomes, not just data assets.
- Participate actively in product discovery to ensure segmentation strategies are technically feasible, scalable, and analytically sound.
- Translate business and customer questions into durable data models and segmentation frameworks.
Machine Learning
- Strong experience in Machine Learning engineering, leveraging ML models to build Segmentation strategies
- Experience operationalizing ML-driven segmentation, including integrating segmentation outputs into other products
- Collaborating with data scientists
- managing standards for model life cycle, monitoring drift, retraining, etc.
- Understanding of Azure ML (or any other cloud) workspaces and integrating them with Azure pipelines
Data Platform & Segmentation Architecture
- Define and evolve the segmentation architecture across customer and commercial data domains.
- Design scalable data models that support real-time, near real time, and batch segmentation use cases.
- Ensure segmentation logic is reusable, explainable, and consistent across channels and products.
- Make explicit trade-offs across latency, accuracy, cost, privacy, and maintainability.
Engineering Execution & Data Quality
- Build and maintain high-quality, production-grade data pipelines and services.
- Ensure strong standards for data quality, lineage, observability, and reliability.
- Reduce fragmentation and duplication in segmentation logic across teams.
- Leverage metrics to continuously improve data freshness, accuracy, and usability.
Individual Contributor Technical Leadership
- Act as a go-to expert for data platform and segmentation design.
- Lead complex technical initiatives end-to-end through hands-on contribution.
- Influence technical direction through design reviews, reference implementations, and documented standards.
- Mentor senior engineers and Tech Leads through coaching and technical guidance (without direct management responsibility).
Microsoft Azure Data Platform & Fabric Expertise
- Demonstrate deep, hands-on expertise with Microsoft Azure data services and their application in large-scale, product-centric environments.
- Design and evolve segmentation and data platform architectures leveraging Azure Data Fabric concepts, ensuring interoperability, governance, and reuse across domains.
- Apply strong architectural judgment across core Azure data products, including data ingestion, storage, processing, analytics, and activation layers.
- Optimize designs across cost, performance, latency, and scalability, using Azure-native capabilities and patterns.
- Ensure secure-by-design implementations aligned with Azure identity, access, encryption, and compliance controls.
- Partner with enterprise architecture, cloud, and security teams to ensure Azure data platform decisions align with broader enterprise strategy while preserving team autonomy.
- Stay current on Azure data platform evolution and proactively assess new capabilities for business value, not novelty.
Business Partnership & Communication
- Serve as a trusted technical partner to Customer and Commercial stakeholders.
- Communicate segmentation concepts, assumptions, and limitations in clear business language.
- Proactively surface data constraints, privacy considerations, and trade-offs to enable informed decisions.
- Support external partner and vendor conversations as a technical authority when needed.
Governance, Privacy & Compliance
- Ensure segmentation approaches comply with data privacy, consent, and regulatory requirements.
- Collaborate with Security, Privacy, and Legal teams to embed governance into platform design—not bolt it on later.
- Advocate for responsible and ethical use of customer and commercial data.
Success Measures
- Segmentation capabilities measurably improve customer engagement and commercial outcomes.
- Reduced duplication and inconsistency in segmentation logic across products.
- Improved data quality, freshness, and trustworthiness.
- Faster time-to-insight and activation for product teams.
- Platforms and models that scale with growth while controlling cost and risk.
Leadership Profile
- Outcome-driven, not data for data’s sake
- Deep technical expertise with strong product intuition
- Influences through credibility and clarity, not authority
- Comfortable operating in ambiguity and evolving problem spaces
- Holds a high bar for data quality, ethics, and reliability
Required Experience & Capabilities
- Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
- 8+ years of hands-on experience in data platform, analytics engineering, or backend engineering roles.
- Deep expertise in data modeling, segmentation strategies, and large-scale data systems.
- Strong experience with cloud-native data platforms and modern data tooling.
- Proven ability to partner closely with product and business stakeholders.
- Demonstrated impact as a senior individual contributor on complex, cross-team initiatives.
Pay Range:
United States: 152,000 - 178,300 USDBase pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
15Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
NoJob Posting End Date:
September 22, 2026Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.Pay Range:: 0 - 0 USD
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:15
Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Long-term Incentive Reference Value Percentage:0 - 20
Long-term Incentive reference value is a market-based competitive value for your role.
The Senior Manager, Software Engineer, Data Platform & Segmentation is a senior individual contributor accountable for the technical vision, design, and evolution of data platforms and segmentation capabilities that power Customer and Commercial product teams operating under a modern Product Operating Model.
This role functions as a hands-on technical leader and multiplier, shaping how customer, commercial, and behavioral data is modeled, segmented, and activated across products, enabling better decisions, personalization, and measurable business outcomes.
The role emphasizes deep technical expertise, product partnership, and architectural leadership, rather than people management.
Core Accountabilities
Product Model & Discovery Partnership
- Partner closely with Product Managers, Designers, and Tech Leads to co-own outcomes, not just data assets.
- Participate actively in product discovery to ensure segmentation strategies are technically feasible, scalable, and analytically sound.
- Translate business and customer questions into durable data models and segmentation frameworks.
Machine Learning
- Strong experience in Machine Learning engineering, leveraging ML models to build Segmentation strategies
- Experience operationalizing ML-driven segmentation, including integrating segmentation outputs into other products
- Collaborating with data scientists
- managing standards for model life cycle, monitoring drift, retraining, etc.
- Understanding of Azure ML (or any other cloud) workspaces and integrating them with Azure pipelines
Data Platform & Segmentation Architecture
- Define and evolve the segmentation architecture across customer and commercial data domains.
- Design scalable data models that support real-time, near real time, and batch segmentation use cases.
- Ensure segmentation logic is reusable, explainable, and consistent across channels and products.
- Make explicit trade-offs across latency, accuracy, cost, privacy, and maintainability.
Engineering Execution & Data Quality
- Build and maintain high-quality, production-grade data pipelines and services.
- Ensure strong standards for data quality, lineage, observability, and reliability.
- Reduce fragmentation and duplication in segmentation logic across teams.
- Leverage metrics to continuously improve data freshness, accuracy, and usability.
Individual Contributor Technical Leadership
- Act as a go-to expert for data platform and segmentation design.
- Lead complex technical initiatives end-to-end through hands-on contribution.
- Influence technical direction through design reviews, reference implementations, and documented standards.
- Mentor senior engineers and Tech Leads through coaching and technical guidance (without direct management responsibility).
Microsoft Azure Data Platform & Fabric Expertise
- Demonstrate deep, hands-on expertise with Microsoft Azure data services and their application in large-scale, product-centric environments.
- Design and evolve segmentation and data platform architectures leveraging Azure Data Fabric concepts, ensuring interoperability, governance, and reuse across domains.
- Apply strong architectural judgment across core Azure data products, including data ingestion, storage, processing, analytics, and activation layers.
- Optimize designs across cost, performance, latency, and scalability, using Azure-native capabilities and patterns.
- Ensure secure-by-design implementations aligned with Azure identity, access, encryption, and compliance controls.
- Partner with enterprise architecture, cloud, and security teams to ensure Azure data platform decisions align with broader enterprise strategy while preserving team autonomy.
- Stay current on Azure data platform evolution and proactively assess new capabilities for business value, not novelty.
Business Partnership & Communication
- Serve as a trusted technical partner to Customer and Commercial stakeholders.
- Communicate segmentation concepts, assumptions, and limitations in clear business language.
- Proactively surface data constraints, privacy considerations, and trade-offs to enable informed decisions.
- Support external partner and vendor conversations as a technical authority when needed.
Governance, Privacy & Compliance
- Ensure segmentation approaches comply with data privacy, consent, and regulatory requirements.
- Collaborate with Security, Privacy, and Legal teams to embed governance into platform design—not bolt it on later.
- Advocate for responsible and ethical use of customer and commercial data.
Success Measures
- Segmentation capabilities measurably improve customer engagement and commercial outcomes.
- Reduced duplication and inconsistency in segmentation logic across products.
- Improved data quality, freshness, and trustworthiness.
- Faster time-to-insight and activation for product teams.
- Platforms and models that scale with growth while controlling cost and risk.
Leadership Profile
- Outcome-driven, not data for data’s sake
- Deep technical expertise with strong product intuition
- Influences through credibility and clarity, not authority
- Comfortable operating in ambiguity and evolving problem spaces
- Holds a high bar for data quality, ethics, and reliability
Required Experience & Capabilities
- Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
- 8+ years of hands-on experience in data platform, analytics engineering, or backend engineering roles.
- Deep expertise in data modeling, segmentation strategies, and large-scale data systems.
- Strong experience with cloud-native data platforms and modern data tooling.
- Proven ability to partner closely with product and business stakeholders.
- Demonstrated impact as a senior individual contributor on complex, cross-team initiatives.
Pay Range:
United States: 152,000 - 178,300 USDBase pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
15Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
NoJob Posting End Date:
September 22, 2026Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.Pay Range:: 0 - 0 USD
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:15
Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Long-term Incentive Reference Value Percentage:0 - 20
Long-term Incentive reference value is a market-based competitive value for your role.
See All 20 Machine Learning Jobs in Atlanta
Find roles in Atlanta that match your experience and apply in just a few clicks.
Find Machine Learning JobsMachine Learning Job Market in Atlanta
Who's Hiring
Top Industries Hiring
- Technology & Software
Machine Learning Jobs in Atlanta: Frequently Asked Questions
How do I get a machine learning job in Atlanta?
Atlanta's machine learning market is strongest in fintech, health tech, and enterprise cloud services, with hiring concentrated in Midtown and Buckhead. Candidates who stand out typically bring experience with production ML systems, not just research or notebook work. Familiarity with the data infrastructure common in financial services or clinical analytics gives a real edge in this market over generalist profiles.
Which companies hire machine learnings in Atlanta?
Employers hiring machine learnings in Atlanta right now include The Home Depot, The Coca-Cola Company, and Worldpay, based on current listings on Migrate Mate as of September 2026. Atlanta's hiring mix includes large financial institutions, health systems, and a growing tier of mid-size SaaS and data platform companies that have relocated or expanded their engineering teams here.
Are there remote machine learning jobs in Atlanta?
Yes, though availability varies by role type. About 80% of machine learning openings tied to Atlanta are remote or hybrid as of September 2026, reflecting how common fully desk-based and analytical work is in this field. In Atlanta specifically, roles at SaaS companies and data consultancies tend to offer the most flexibility, while positions at banks and health systems more often require on-site presence.
How can I get a machine learning job in Atlanta with little or no experience?
The most realistic entry path in Atlanta is through data analyst or analytics engineer roles at mid-size fintech or health tech companies, where ML work is adjacent and employers are more open to growing talent internally. Atlanta's Georgia Tech pipeline means many teams are accustomed to hiring recent graduates into junior ML or data science roles. Building a portfolio with real datasets, contributing to open-source projects, and targeting companies in growth stages rather than large enterprises improves your odds significantly.
Which industries hire the most machine learnings in Atlanta?
The sectors hiring the most machine learnings in Atlanta are Technology & Software, based on current listings on Migrate Mate as of September 2026. Atlanta's role as a major hub for payment processing, insurance technology, and hospital systems means those industries consistently generate the highest volume of ML openings in the city.
See All 20 Machine Learning Jobs in Atlanta
Find roles in Atlanta that match your experience and apply in just a few clicks.
Find Machine Learning Jobs