Machine Learning Intern Jobs in Atlanta, GA
Machine Learning Intern jobs in Atlanta are in strong demand, concentrated in Midtown, Buckhead, and the Technology Square corridor across fintech, healthcare tech, and enterprise software. Employers hiring right now include The Coca-Cola Company, The Home Depot, and Speria. Find a role that fits below and apply directly.
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Showing 5 of 13+ Machine Learning Intern 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 13 Machine Learning Intern Jobs in Atlanta
Find roles in Atlanta that match your experience and apply in just a few clicks.
Find Machine Learning Intern JobsMachine Learning Intern Job Market in Atlanta
Who's Hiring
Top Industries Hiring
- Technology & Software
Machine Learning Intern Jobs in Atlanta: Frequently Asked Questions
How do I get a machine learning intern job in Atlanta?
The strongest path into machine learning intern roles in Atlanta is targeting the city's fintech, health tech, and enterprise software employers, which cluster around Midtown and Technology Square near Georgia Tech. Candidates with Python, TensorFlow, or data pipeline experience stand out locally. Applying directly to Atlanta-based startups and mid-size tech firms, rather than only large corporations, often moves faster in this market.
Which companies hire machine learning interns in Atlanta?
Atlanta machine learning intern roles are posted by The Coca-Cola Company, The Home Depot, and Speria and others right now, based on current listings on Migrate Mate as of September 2026. Atlanta's employer mix includes Fortune 500 companies with regional headquarters, fast-growing fintech and health tech startups, and research-driven organizations tied to the university ecosystem.
Are there remote machine learning intern jobs in Atlanta?
Yes, though availability depends on the role: model training, data labeling, and analytical work tend to be remote-compatible, while roles involving lab infrastructure or on-site GPU clusters typically require in-person presence. About 100% of machine learning intern openings tied to Atlanta are remote or hybrid as of September 2026, and the research and analytics-focused roles in Atlanta's tech sector skew toward flexible arrangements.
How can I get a machine learning intern job in Atlanta with little or no experience?
The most realistic entry path in Atlanta is applying to internship programs at mid-size fintech and health tech companies, which often hire candidates with strong academic projects and GitHub portfolios rather than prior industry experience. Georgia Tech's student pipelines and Atlanta-based startup accelerators like Atlanta Tech Village regularly surface early-career opportunities. Demonstrating hands-on projects in Python or scikit-learn closes the experience gap faster than additional coursework alone.
Which industries hire the most machine learning interns in Atlanta?
The sectors hiring the most machine learning interns in Atlanta are Technology & Software, based on current listings on Migrate Mate as of September 2026. Atlanta's position as a regional hub for financial services, healthcare systems, and logistics technology drives consistent demand for machine learning talent at the intern level.
See All 13 Machine Learning Intern Jobs in Atlanta
Find roles in Atlanta that match your experience and apply in just a few clicks.
Find Machine Learning Intern Jobs