ZipRecruiter

Log In

1

Senior Machine Learning Engineer Jobs in Atlanta, GA

Speria

Machine Learning Operations Engineer

Atlanta, GA · On-site

$120 - $180/hr

... work with senior and executive management. Job Summary We are seeking a highly skilled and ... The MLOps Engineer works closely with Machine Learning Engineers and Data Engineers to ensure that ...

Coca-Cola

Senior Machine Learning Architect

Atlanta, GA

$124K - $169K/yr

... learning (classification and regression), Bayesian modeling, forecasting, and unsupervised ... Proficientexperiencewithanalytical and programming languages and packages, such as Python, R, and ...

Omaze

Staff Machine Learning Engineer - Search

Atlanta, GA · On-site

$159 - $208.95/hr

As a Staff Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will own critical production ML systems across ...

Coca-Cola

Junior Machine Learning Engineer

Atlanta, GA · On-site

... Programming (MIP), supervised learning (classification and regression), Bayesian modeling, forecasting, and unsupervised clustering and putting solutions into production. * Strong aptitude for ...

Coca-Cola HBC

Junior Machine Learning Engineer

Atlanta, GA · On-site

$97 - $115/hr

... Programming (MIP), supervised learning (classification and regression), Bayesian modeling, forecasting, and unsupervised clustering and putting solutions into production. * Strong aptitude for ...

New

previous page

Showing results 41-60

All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Atlanta, GA

Senior Machine Learning Engineer information

See Atlanta, GA salary details

$57.2K

$121.7K

$176.5K

How much do senior machine learning engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for senior machine learning engineer in Atlanta, GA is $121,704.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $138,000.00 per year, depending on experience, location, and employer.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Atlanta, GA? The most popular types of Machine Learning Engineer jobs in Atlanta, GA are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Atlanta, GA? For Senior Machine Learning Engineer jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Atlanta, GA look for? The top searched job categories for Senior Machine Learning Engineer jobs in Atlanta, GA are:
What cities near Atlanta, GA are hiring for Senior Machine Learning Engineer jobs? Cities near Atlanta, GA with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $121,704 per year, or $58.5 per hour.

Machine Learning Engineer 3 (AI Engineer)

4pconsultinginc

Atlanta, GA • On-site

Contractor

Re-posted 27 days ago

Job description

Machine Learning Engineer 3 (AI Engineer)

Location: Atlanta, GA

Client- Southern Company Gas

Contract- 1 Year
 

Job Summary

We are seeking a highly skilled Machine Learning Engineer (Level 3) with 5–10 years of experience to design, develop, and deploy advanced AI models and systems. This role requires expertise in machine learning, data analysis, and model deployment to optimize business operations and drive innovation within the utilities and energy sector.

The successful candidate will collaborate with cross-functional teams—including data scientists, engineers, and business stakeholders—to integrate AI solutions into real-world applications that support operational efficiency, customer service, and sustainability initiatives.

Key Responsibilities

  • AI Model Development: Design and implement machine learning models and algorithms to address utility-specific challenges such as grid optimization, asset reliability, predictive maintenance, and customer analytics.

  • Data Analysis: Analyze large, complex datasets from SCADA, AMI, and IoT systems to extract actionable insights.

  • Model Training & Evaluation: Train, test, and validate AI models to ensure accuracy, scalability, and compliance with industry reliability standards.

  • Deployment & Integration: Deploy AI solutions into production systems and integrate with enterprise platforms (e.g., Azure, Maximo, EMS/DMS systems).

  • Innovation: Stay current with the latest advancements in AI/ML and recommend solutions that can enhance grid resilience, safety, and efficiency.

  • Collaboration: Partner with engineering, IT, and business units to define requirements and deliver business-aligned AI solutions.

  • Performance Monitoring: Continuously monitor AI models and refine as needed to maintain performance and compliance.

  • Documentation & Knowledge Sharing: Create clear documentation of models, workflows, and processes for reuse and compliance.

Qualifications

Education:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.

Experience:

  • 5–10 years of experience in AI, ML, or data science roles, with proven success in AI model development and deployment.

  • Industry experience in utilities, energy, or large-scale infrastructure data is preferred.

Technical Skills:

  • Proficiency in Python, R, or Java.

  • Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn.

  • Strong grasp of data structures, algorithms, and applied statistics.

  • Familiarity with cloud platforms such as Azure ML and Azure Databricks (preferred), AWS or Google Cloud (a plus).

  • Experience with big data tools (e.g., Spark, Hadoop) is desirable.

  • Exposure to natural language processing (NLP) or computer vision a plus.

Soft Skills:

  • Strong analytical and problem-solving abilities.

  • Excellent communication skills for cross-functional collaboration.

  • Ability to work independently and manage multiple projects simultaneously.

  • Experience working in agile or iterative development environments.

Preferred Qualifications

  • Lighting up AI/ML use cases in the utility/energy sector (e.g., outage prediction, DERMS optimization, vegetation management analytics).

  • Certifications in AI/ML, data science, or cloud platforms (Azure, AWS, GCP).

  • Experience with MLOps pipelines and CI/CD integration for model deployment.