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Mlops Machine Learning Engineer Jobs in Georgia (NOW HIRING)

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do ... MLOps & Infrastructure Champion MLOps best practices: model versioning, champion/challenger ...

Machine Learning Engineer

Alpharetta, GA

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... the machine learning function at a market-leading insurance company. As one of the first data ... Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.

CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... Understanding of FDA regulatory requirements for AI/ML in medical devices Experience with MLOps ...

Lead Machine Learning Engineer - REMOTE

Atlanta, GA · Remote

$98K - $129K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Join a Company that Empowers you to Build your Future Lennar is seeking a Machine Learning Engineer ... The ideal candidate is a software engineer with deep MLOps expertise. They know how to design model ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162K - $342K/yr

  • Medical

  • Retirement

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Machine Learning Engineer

Atlanta, GA · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Showing results 21-40

Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What cities in Georgia are hiring for Mlops Machine Learning Engineer jobs?

Cities in Georgia with the most Mlops Machine Learning Engineer job openings:

Senior Machine Learning Engineer (MLOPS)

Coca-Cola

Atlanta, GA

$100K - $138K/yr

Full-time

Posted 11 days ago


Coca-Cola rating

7.6

Company rating: 7.6 out of 10

Based on 441 frontline employees who took The Breakroom Quiz

139th of 440 rated food and drinks producers


Job description

Job Description Summary:

The Coca-Cola Company's Technology organization isin the midst ofa digital transformation that allows our employees to use world class technology to connect our products to our customers all over the world. This journey is a very exciting time forCoca-Colaand our employees are big contributors to our Success and Growth. Our large scale and complex environmentoffersan incredible opportunity to address challenges, enable innovative solutions to make a difference for our customers.

In this position, you will embark on a journey of leveraging vast amounts of data to transform it into actionable insights. You will aid in the development of analytics models and work under the guidance of seasoned data science professionals to drive decision-making and strategyacross the organization. This is an exciting opportunity togrow in your career in data science and analytics within a supportive and innovative environment.

What You'll Do for Us:

  • Model Deployment & Operationalization: Partner with data science teams to transition machine learning models from experimentation to production environments, packaging models into robust Docker containers for scalable and reproducible deployments.

  • Pipeline Automation: Build and maintain automated CI/CD pipelines for machine learning workflows (e.g., model training, evaluation, and deployment) utilizing tools like GitHub Actions. Leverage Azure Container Registry to securely manage container images and deploy scalable workloads to Azure Kubernetes Service (AKS) or Azure Container Instances (ACS).

  • Utilize Azure Machine Learning and Microsoft Fabric Data Science to manage the ML lifecycle. Adapt prior experience from other cloud platforms to effectively navigate and optimize our current stack.

  • Monitoring & Maintenance: Implement monitoring solutions to track model performance, data drift, and system health in production. Ensure comprehensive logging and observability for containerized model endpoints running on Kubernetes clusters. Troubleshoot and resolve operational issues as they arise.

  • Data Integration: Collaborate with data engineering teams to ensure clean, reliable data pipelines (such as Medallion architectures) seamlessly feed into machine learning models.

  • Engineering Best Practices: Write clean, modular, and testable code (primarily in Python) while adhering to version control best practices using Git.

  • Mentor, guide, and develop junior/aspiringMLOpsEngineeracross the organization.

  • Lead continuous career development and drive engineering excellence through performance reviews.

Qualifications& Requirements:

  • 6+years of professional experience (or equivalent strong academic/internship experience) inMLOps, Data Engineering, Software Engineering, or a related field.

  • 3+ years of experience managing and scaling high-performingMLOpsor data platform teams, with a focus on career development, performance management, and technical mentorship.

  • Cloud ML Platforms: Hands-on experience with at least one major cloud ML platform. While Azure ML and Microsoft Fabric are preferred, experience with AWS SageMaker, GCP Vertex AI, or similar platforms is highly acceptable.

  • Programming: Strong proficiency in Python for scripting, automation, and model deployment.

  • DevOps & Containerization: Familiarity with version control (Git), building CI/CD pipelines (e.g., GitHub Actions, Azure DevOps), and containerization ecosystems (Docker, Azure Container Registry, Kubernetes/AKS/ACS).

  • Foundational Knowledge: A solid understanding of the machine learning lifecycle, containerized microservices architectures, and fundamental software engineering principles.

Functional Skills:

Practical experience with as many of the following as possible:

  • Handles multiple competing priorities in a fast-paced, deadline-driven environment

  • Strong attention to details and excellent problem-solving skills

  • Ability to work in a collaborative team environment

  • Highly innovative, adaptable, and self-directed

  • Results-oriented with a delivery focus

  • Presentation skills: Ability to communicate technical topics to business audience.

  • Be able to collaborate across other levels of the organization

  • Team player who can lead a discussion to defined outcomes

  • Effective Communication

  • Pursuing Innovation

What We Can Do for You:

  • Innovation & Technology:The ability to work with an award-winning team that is on the cutting edge of innovation.

  • Exposure to World Class Leaders:Availability to global technology leaders that will expand your network and exposure you to emerging technologies and techniques.

  • Agile Work Environment:We embrace agile with management that believes in removing barriers, so you are empowered to experiment, iterate and innovate.

Our 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.

The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States.

Skills:

Pay Range:

United States of America: 143,400 USD - 169,300 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.

Location(s):

United States of America

City/Cities:

Atlanta

Travel Required:

00% - 25%

Relocation Provided:

No

Job Posting End Date:

August 20, 2026

Our 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 Visionto 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.

What Coca-Cola employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Coca-Cola logo

About Coca-Cola

Sourced by ZipRecruiter

On May 8, 1886, Dr. John Pemberton brought his perfected syrup to Jacobs' Pharmacy in downtown Atlanta where the first glass of Coca‑Cola was poured. From that one iconic drink, we’ve evolved into a total beverage company. More than 2.2 billion servings of our drinks are enjoyed in more than 200 countries and territories each day. We are constantly transforming our portfolio, from reducing added sugar in our drinks to bringing innovative new products to market. We seek to positively impact people’s lives, communities and the planet through water replenishment, packaging recycling, sustainable sourcing practices and carbon emissions reductions across our value chain. Together with our bottling partners, we employ more than 700,000 people, helping bring economic opportunity to local communities worldwide. We are committed to offering people more of the drinks they want across a range of categories and sizes while driving sustainable solutions that build resilience into our business and create positive change for the planet.

Industry

Food services and drinking places and food and drink manufacturing

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US