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Aws Machine Learning Jobs in Atlanta, GA (NOW HIRING)

innovitusa

Machine Learning Engineer

Atlanta, GA · On-site

W2 Candidates Only We are seeking a Machine Learning Engineer to develop, deploy, and optimize ... AWS SageMaker or Azure ML * MLflow * Docker and Kubernetes * MLOps * Experience with AI/ML ...

Cox Automotive

Machine Learning Lead Engineer

Morrow, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training ...

Cox Automotive

Machine Learning Lead Engineer

Smyrna, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training ...

Cox Automotive

Machine Learning Lead Engineer

Austell, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training ...

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Aws Machine Learning information

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How much do aws machine learning jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for aws machine learning in Atlanta, GA is $67.37, according to ZipRecruiter salary data. Most workers in this role earn between $59.86 and $78.61 per hour, depending on experience, location, and employer.

What is an AWS Machine Learning?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

What does an AWS Machine Learning do?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.

What are the key skills and qualifications needed for an AWS Machine Learning?

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

Does AWS use machine learning?

AWS offers a wide range of machine learning services and tools, such as Amazon SageMaker, which enable developers and data scientists to build, train, and deploy machine learning models. As a cloud provider, AWS integrates machine learning into its infrastructure to support various applications, making it a key platform for machine learning professionals. Knowledge of AWS services and machine learning concepts is valuable for roles like AWS Machine Learning specialists.

Is AWS Machine Learning a high paying job?

AWS Machine Learning roles are generally well-paid due to the specialized skills required, such as expertise in cloud computing, data science, and machine learning frameworks. Salaries vary based on experience, location, and certifications, but they tend to be higher than average for tech roles with similar responsibilities.

What are the most commonly searched types of Aws Machine Learning jobs in Atlanta, GA?

The most popular types of Aws Machine Learning jobs in Atlanta, GA are:

What are popular job titles related to Aws Machine Learning jobs in Atlanta, GA?

For Aws Machine Learning jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Aws Machine Learning jobs in Atlanta, GA look for?

The top searched job categories for Aws Machine Learning jobs in Atlanta, GA are:

Aws Machine Learning jobs near you
Infographic showing various Aws Machine Learning job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $140,137 per year, or $67.4 per hour.

Machine Learning Engineer

innovitusa

Atlanta, GA • On-site

Contractor

Posted 12 days ago

Job description

Hiring: W2 Candidates Only

Job Description:
We are seeking a Machine Learning Engineer to develop, deploy, and optimize machine learning models and AI solutions. The ideal candidate will have strong experience with Python, machine learning frameworks, data processing, and cloud-based ML platforms.

Required Skills:

  • 5+ years of Machine Learning experience
  • Python
  • Scikit-learn
  • TensorFlow or PyTorch
  • Machine Learning algorithms
  • Pandas and NumPy
  • SQL
  • Model development and evaluation
  • Data preprocessing
  • Model deployment

Preferred Skills:

  • Generative AI
  • Large Language Models (LLMs)
  • NLP
  • Hugging Face
  • AWS SageMaker or Azure ML
  • MLflow
  • Docker and Kubernetes
  • MLOps
  • Experience with AI/ML production environments

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