MLOps Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer, contract length unspecified, offering a competitive pay rate. Key skills include AWS services, Docker, Kubernetes, CI/CD pipelines, Python programming, and machine learning frameworks. Data engineering experience is a plus.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 30, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Atlanta, GA
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🧠 - Skills detailed
#Infrastructure as Code (IaC) #Kubernetes #Jenkins #Docker #AWS (Amazon Web Services) #IAM (Identity and Access Management) #S3 (Amazon Simple Storage Service) #TensorFlow #Data Lake #Deployment #Lambda (AWS Lambda) #Data Engineering #Python #EC2 #SageMaker #"ETL (Extract #Transform #Load)" #Programming #ML (Machine Learning) #GitLab #PyTorch #Cloud
Role description
• Strong expertise in AWS Cloud services: EC2, S3, Lambda, SageMaker, CloudFormation, CloudWatch, IAM, EKS, etc.
• Hands-on experience with AWS Cloud Development Kit (CDK) for Infrastructure as Code.
• Solid understanding of machine learning lifecycle and deployment challenges.
• Proficiency with containerization (Docker) and orchestration (Kubernetes, EKS).
• Experience building CI/CD pipelines with tools like Jenkins, GitLab CI, or AWS CodePipeline.
• Programming experience in Python and familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Knowledge of data engineering concepts and tools (ETL, data lakes, streaming) is a plus.
• Strong expertise in AWS Cloud services: EC2, S3, Lambda, SageMaker, CloudFormation, CloudWatch, IAM, EKS, etc.
• Hands-on experience with AWS Cloud Development Kit (CDK) for Infrastructure as Code.
• Solid understanding of machine learning lifecycle and deployment challenges.
• Proficiency with containerization (Docker) and orchestration (Kubernetes, EKS).
• Experience building CI/CD pipelines with tools like Jenkins, GitLab CI, or AWS CodePipeline.
• Programming experience in Python and familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Knowledge of data engineering concepts and tools (ETL, data lakes, streaming) is a plus.
