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Machine Learning Engineer Jobs in Athens, GA (NOW HIRING)

Microsoft Fabric Data Engineer

Athens, GA · On-site

$110K - $132K/yr

Data Engineer / Fabric Administrator The primary role of the Data Engineer / Fabric Administrator is to design, develop, and maintain modern data solutions within Microsoft Fabric, supporting the ...

Data Engineer

Athens, GA · On-site

$95K - $115K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Showing results 41-45

Machine Learning Engineer information

See Athens, GA salary details

$30.4K

$124.3K

$186.8K

How much do machine learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for machine learning engineer in Athens, GA is $124,338.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $149,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are popular job titles related to Machine Learning Engineer jobs in Athens, GA?

For Machine Learning Engineer jobs in Athens, GA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Athens, GA look for?

The top searched job categories for Machine Learning Engineer jobs in Athens, GA are:

What cities near Athens, GA are hiring for Machine Learning Engineer jobs?

Cities near Athens, GA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Athens, GA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $124,338 per year, or $59.8 per hour.

$110K - $132K/yr

Full-time

Posted 4 days ago


Job description

Job Description

Data Engineer / Fabric Administrator

The primary role of the Data Engineer / Fabric Administrator is to design, develop, and maintain modern data solutions within Microsoft Fabric, supporting the organization's analytics, reporting, automation, and AI initiatives. This position is responsible for building secure and scalable data pipelines, managing data throughout the medallion architecture, developing semantic models and Power BI reporting solutions, and ensuring data is governed and protected throughout its lifecycle. The ideal candidate will possess strong technical expertise in data engineering, analytics, and Microsoft Fabric technologies, along with excellent problem-solving, communication, and collaboration skills. The successful candidate will demonstrate a security-first mindset and the ability to work independently in a rapidly evolving environment.

Reports to: Senior Director of Data Management and Security

Direct Reports: None

Duties/Responsibilities: The duties listed below are an outline of role's responsibilities and should not be considered an all-inclusive list. As the needs of the organization change, these duties may be modified as needed.

  • Develop, maintain, and optimize data solutions within Microsoft Fabric, including data ingestion, transformation, modeling, and reporting.
  • Design and support data pipelines aligned with the medallion architecture, including Bronze, Silver, and Gold data layers.
  • Build and maintain Lakehouses, Warehouses, Dataflows, Data Factory pipelines, Notebooks, and other Fabric components.
  • Create and maintain Power BI dashboards, reports, semantic models, and visualizations that support business decision-making.
  • Partner with business stakeholders to gather requirements, understand reporting needs, and translate business questions into actionable analytics solutions.
  • Develop secure and reliable data models that support role-based access controls, governance requirements, and data classification standards.
  • Apply security-first development principles, including least-privilege access, secure coding practices, data protection controls, and appropriate handling of sensitive information.
  • Collaborate with Information Technology, Security, Compliance, and business teams to ensure data solutions align with organizational standards and objectives.
  • Support testing, validation, deployment, monitoring, troubleshooting, documentation, and continuous improvement of data pipelines and reporting assets.
  • Develop and maintain reusable frameworks, development standards, and engineering best practices within the Microsoft Fabric platform.
  • Utilize automation and AI-assisted development tools responsibly to improve productivity while maintaining security, code quality, and platform reliability.
  • Evaluate new technologies and recommend enhancements that improve data accessibility, reporting capabilities, automation, and analytics maturity.
  • Ensure solutions adhere to security, compliance, and data governance standards.
  • Stay current with emerging trends and technologies in data engineering, analytics, Microsoft Fabric, Power BI, and artificial intelligence.

Education & Experience

  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, Software Engineering, or a related field.
  • At least 3 years of hands-on experience in data engineering, business intelligence, analytics development, or a related technical role.
  • Experience developing solutions within Microsoft Fabric, Microsoft Power Platform, Power BI, SQL-based environments, or similar enterprise analytics platforms.
  • Experience designing and supporting data pipelines, data models, and reporting solutions.

Preferred Knowledge, Skills, & Abilities.

  • Hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, Data Factory, Dataflows, Notebooks, and related Fabric services.
  • Strong understanding of medallion architecture and data lifecycle management.
  • Experience developing Power BI reports, dashboards, semantic models, and DAX calculations.
  • Proficiency with SQL and data transformation concepts.
  • Experience working with structured and semi-structured data from multiple business systems.
  • Familiarity with Python, PySpark, Spark notebooks, or related data engineering technologies.
  • Understanding of data governance, data lineage, metadata management, and data quality processes.
  • Knowledge of Microsoft Purview, data classification, sensitivity labeling, and data loss prevention concepts.
  • Familiarity with GitHub, source control, CI/CD methodologies, and DevOps practices.
  • Strong analytical and problem-solving skills.
  • Excellent verbal and written communication skills.
  • Ability to communicate technical concepts effectively to non-technical stakeholders.
  • Strong organizational skills and ability to manage multiple priorities.
  • Ability to work independently and collaboratively across departments.
  • Commitment to secure development practices and protecting company data.

Work Environment

  • The work environment characteristics described herein are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The noise level in the work environment is usually moderate.
  • Travel: May require travel to sites as needed, around 10%

Physical Demands:

  • The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
  • While performing the duties of this job, the employee is frequently required to stand; walk; sit; use hands to finger, handle, or feel; reach with hands and arms; climb or balance; stoop, kneel, crouch, or crawl and talk or hear.
  • Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception, and the ability to adjust focus.
  • The employee may infrequently drive a vehicle (intrastate and interstate travel) or be subject to air travel for purposes of Company business.

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Landmark Properties is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.