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Ml Engineer Jobs in Georgia (NOW HIRING)

Chenega Corporation

AI/ML Engineer

Atlanta, GA · On-site

$110 - $120/hr

Chenega Services &FederalSolutions, LLC , a Chenega Professional Services' company, is looking for a AI/ML Engineer . In this role, you'll serve as a strategic AI technical lead supporting the ...

Waystar, Inc

Senior ML Engineer

Atlanta, GA · On-site

$100 - $160/hr

Job Summary We are seeking a highly skilled and innovative Machine Learning Engineer to develop end‑to‑end ML pipelines, fine‑tune language models, design agentic architectures, and deploy ...

CBRE

Senior Principal AI/ML Engineer

Atlanta, GA · On-site

$120K - $166K/yr

Role Summary The Senior AI/ML Engineer is a hands-on technical practitioner responsible for designing, building, and operationalizing production-grade AI and machine learning systems that power ...

Waystar, Inc

Senior ML Engineer II

Atlanta, GA · On-site

$120 - $160/hr

Overview We are seeking a highly skilled and innovative Senior ML Engineer with a passion for building robust, efficient, and domain‑specific AI systems using Language Models (LMs) and agentic ...

Waystar

Senior ML Engineer

Atlanta, GA · On-site

$100K - $138K/yr

They are seeking a Senior Machine Learning Engineer to develop robust AI systems utilizing Language Models and agentic architectures, focusing on the entire ML pipeline from data extraction to ...

Worldpay

Senior ML Software Engineer

Atlanta, GA · On-site

$117K - $155K/yr

We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross ...

Onsite It Advisors LLC

Be Seen First

AI/ML Senior Software Engineer

Atlanta, GA · On-site

$80 - $91/hr

Team is seeking an AI/ML Engineer. In this role, you'll serve as a strategic AI technical lead supporting the modernization of public health platforms through the design, development, and deployment ...

Onsite It Advisors LLC

Be Seen First

AI/ML Senior Software Engineer

Atlanta, GA · On-site

$80 - $91/hr

Team is seeking an AI/ML Engineer. In this role, you'll serve as a strategic AI technical lead supporting the modernization of public health platforms through the design, development, and deployment ...

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Showing results 21-40

All JobsMl Engineer JobsMl Engineer Jobs in Georgia

Ml Engineer information

See Georgia salary details

$27.9K

$75.3K

$119.9K

How much do ml engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for ml engineer in Georgia is $75,305.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,200.00 and $92,000.00 per year, depending on experience, location, and employer.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

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

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

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

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often work in environments that emphasize continuous learning and adaptation. The demand is expected to remain strong as organizations increasingly rely on machine learning solutions for competitive advantage.

What does a machine learning engineer do?

A machine learning engineer designs, develops, and deploys machine learning models to solve specific problems using large datasets. They work with programming languages like Python or Java, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and software engineers to integrate models into applications.

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

The most popular types of Ml Engineer jobs in Georgia are:

What are popular job titles related to Ml Engineer jobs in Georgia?

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

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

The top searched job categories for Ml Engineer jobs in Georgia are:

What cities in Georgia are hiring for Ml Engineer jobs?

Cities in Georgia with the most Ml Engineer job openings:

Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Georgia as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $75,305 per year, or $36.2 per hour.

AI/ML Engineer

Chenega Corporation

Atlanta, GA • On-site

$110 - $120/hr

Other

Posted 5 days ago

Job description

Overview

Position contingent on contract award - details below are subject to change based on final award.

Come join a company that strives forExtraordinary People and Exceptional Performance!Chenega Services &FederalSolutions, LLC, a Chenega Professional Services’ company, is looking for a AI/ML Engineer.

In this role, you'll serve as a strategic AI technical lead supporting the modernization of public health platforms through the design, development, and deployment of advanced AI capabilities. This position integrates cutting‑edge technologies—including AI agents, retrieval‑augmented generation (RAG), and large language models (LLMs)—to enable dynamic interaction with structured and unstructured public health data, drive real-time insights, and strengthen decision-making across mission-critical environments. This position is responsible for architecting and optimizing AI systems, including data modeling for AI agents, memory and state management, RAG pipeline construction, and performance tuning of retrieval processes tailored to public health use cases. The role develops and implements rigorous AI evaluation strategies to ensure high-quality, trustworthy outputs and scalable performance across deployed solutions.

Our company offers employees the opportunity to join a team where there is a robust employee benefits program, management engagement, quality leadership, an atmosphere of teamwork, recognition for performance, and promotion opportunities. We actively strive to channel our highly engaged employee’s knowledge, critical thinking, innovative solutions for our clients.

Responsibilities
  • Integrate cutting‑edge AI technologies—including AI agents—to enhance platform functionality, enable dynamic data interaction, and support real-time insights and decision-making.
  • Develop and implement rigorous AI evaluation strategies to ensure reliability, performance, and continuous improvement across deployed AI solutions.
  • Lead the design of foundational system architecture, including data modeling for AI agents, memory and state management, and construction and optimization of RAG pipelines.
  • Drive performance optimization of retrieval workflows for public health use cases while defining and upholding strict data quality, curation, and documentation standards in collaboration with cross-functional AI teams.
  • Maintain adherence to privacy requirements, anonymization protocols, and ethical guidelines essential to responsible public health data management.
  • Other duties as assigned
Qualifications
  • 8+ years of experience designing, developing, and deploying machine learning models
  • 8+ years of experience with Generative AI, LLMs, or RAG applications
  • 8+ years of hands-on experience with Python for ML and data engineering
  • Experience with Azure
  • Experiencein SQL for data manipulation and feature engineering
  • Knowledge of MLOps tools (MLflow)
  • Ability to support on-site work in Atlanta, GA
  • Ability to obtain andmaintaina Public Trust or Suitability/Fitness determination based on client requirements
  • Bachelor’s degree in technology, Engineering, or Computer Science.
  • Successfully pass background and drug screening.
Teleworking DetailsHybrid - Onsite Work RequiredEstimated Salary/WageUSD $110,000.00/Yr. Up to USD $120,000.00/Yr.
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