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Mlops Jobs in Georgia (NOW HIRING)

DPR Construction

MLOps Engineer

Atlanta, GA · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality, innovative projects. Our team integrates cutting-edge technologies into the construction process to ...

TriNet

Staff MLOps Engineer

Dunwoody, GA · On-site

A Brief Overview As a Staff MLOps Engineer, you will play a pivotal role in designing, implementing, and optimizing machine learning operations within our infrastructure. You will collaborate closely ...

Trinet, Inc

Staff MLOps Engineer

Dunwoody, GA · On-site

A Brief Overview As a Staff MLOps Engineer, you will play a pivotal role in designing, implementing, and optimizing machine learning operations within our infrastructure. You will collaborate closely ...

IT America Inc

DevOps/MLOps Engineer

Cumming, GA · On-site

$47 - $64.50/hr

Position: DevOps/MLOps Engineer Location: Cumming, GA Duration: Long-term contract Note: Final interview will take place onsite--only local candidates will be considered * Our Fintech client is ...

smart folks inc

Lead AI/ML Engineer

Atlanta, GA · On-site

$98K - $129K/yr

Hands-on MLOps & Engineering Practice: * Drive the practical implementation of the MLOps strategy, directly overseeing the construction and optimization of CI/CD pipelines for AI/ML systems using ...

CSAA

MLOps, Automation & Observability * Design and implement automation, monitoring, observability, and operational tooling to improve platform reliability and efficiency. * Develop and maintain ...

New

Coca-Cola

Senior Machine Learning Engineer (MLOPS)

Atlanta, GA · On-site

$100K - $138K/yr

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 ...

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Mlops information

See Georgia salary details

$79K

$123.9K

$147.4K

How much do mlops jobs pay per year?

As of Aug 21, 2026, the average yearly pay for mlops in Georgia is $123,934.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,098.00 and $134,604.00 per year, depending on experience, location, and employer.

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

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

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

Is MLOps outdated?

MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.

What is the average salary in MLOps?

The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.

What are the most commonly searched types of Mlops jobs in Georgia?

The most popular types of Mlops jobs in Georgia are:

What are popular job titles related to Mlops jobs in Georgia?

For Mlops jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Mlops jobs in Georgia look for?

The top searched job categories for Mlops jobs in Georgia are:

What cities in Georgia are hiring for Mlops jobs?

Cities in Georgia with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Georgia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $123,934 per year, or $59.6 per hour.

MLOps Engineer

DPR Construction

Atlanta, GA • On-site

Full-time

Re-posted 21 days ago

DPR Construction rating

8.0

Company rating: 8.0 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

17th of 80 rated construction

Job description

Job DescriptionDPR is looking for an experienced Data and MLOps Engineer to join our Data and AI team and work closely with the Data Platform, BI and Enterprise architecture teams to influence the technical direction of DPR's AI initiatives.
You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas.

MLOps Engineer

DPR is a leading construction company committed to delivering high-quality, innovative projects. Our team integrates cutting-edge technologies into the construction process to streamline operations, enhance decision-making, and drive efficiency at all levels. We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering.

Position Overview

TheMLOps Engineerwill be instrumental inthe designand implementation of scalable, cloud-nativesolutions to meet the growing needs of ourData & Developmentteam.Thesuccessful candidatewill demonstrate the abilitytoabstract complexity andcreatereusable, scalable patternsthat accelerate development.The MLOps Engineerwilldesign, build and support the infrastructureand systemsthat enable our teams to deliver reliable, high-impactdata,workflows, and collaboratingclosely with data engineers, software developers, data scientists and product teams.

Responsibilities

  • Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning

  • Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection

  • Standardize observability practicesacross AI/ML and other development teamsincluding logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms

  • Design and deploy containerized MLworkloads,partnering withInfrastructureEngineering for cluster provisioning and governance

  • Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows

  • Implement AI-driven data validation, schema drift detection, and metadata management.

  • Establish governance frameworks for AI systems, including bias detection, explainability, and auditability

  • Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention

  • Collaborate withInfrastructureEngineering toautomate infrastructure provisioning

  • Act as a technical point of contact forDevOps andMLOps practices,developing reusable patterns, documentation, and proof-of-concepts to drive adoption

Qualifications

  • Bachelor's degree in Computer Science,Data Science,Information Systems, or a related field

  • 5+years of experience inDevOps, MLOps,Data Engineering,Software Engineeringor Site Reliability Engineering

  • Strong understanding of cloudinfrastructure and experience working with at least one major cloudprovider, preferably Azure

  • Proficiencyinat least one objected-oriented programming language, preferably pythonwith hands-on experience inml frameworks like TensorFlow, PyTorch or Scikit-learn

Required Skills

  • Experience with CI/CD processes and automation

  • Experience withInfrastructure as Codetoolssuch as Terraform,Bicep

  • Proficiencyincontainerized application deploymentsand container orchestration- experience with Kubernetes, especially AKS would be a huge plus

  • Experiencestanding up and managingobservability tools such as Datadog, Azure Monitor or GrafanaforAPM, LLM Opsand model performance monitoring

  • Experiencedeploying production-ready machine learning models

  • Experience withModel explainability (SHAP, LIME)or similar

  • Experience with cloud cost management and practices (e.g., Azure Cost Management, chargeback/show back models).

Nice to Have

  • Experience in Azure, particularly AKS,ACR, ARM,App Service, Azure Machine Learning and AI Foundry, Azure Monitor

  • Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines

  • Exposure to managing and monitoring ML workloads that support generative AI or advanced analytics use cases

  • Proficiency with Snowflake

  • Experience with workflow orchestration platforms such as Apache Airflow, Argo Workflow, Prefect, etc.

DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world.

Working at DPR, you'll have the chance to try new things, explore unique paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek.

Explore our open opportunities atwww.dpr.com/careers.

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