MLOps/AWS DevOps Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps/AWS DevOps Engineer on a contract basis, requiring 8+ years of DevOps experience, 2+ years in MLOps, and expertise in AWS. Pay rate and contract length are unspecified. Location is remote.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
September 25, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Unknown
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Houston, TX
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🧠 - Skills detailed
#Security #RDS (Amazon Relational Database Service) #Data Science #Deployment #Terraform #SageMaker #EC2 #Kubernetes #AWS (Amazon Web Services) #DevOps #Computer Science #Infrastructure as Code (IaC) #Monitoring #Bash #GitHub #S3 (Amazon Simple Storage Service) #AWS DevOps #AI (Artificial Intelligence) #Model Deployment #Automation #YAML (YAML Ain't Markup Language) #ML (Machine Learning) #Cloud #JSON (JavaScript Object Notation) #Scripting #Docker #Lambda (AWS Lambda) #Web Services #Python
Role description
We're looking for a skilled MLOps/DevOps Engineer to join our team as a contractor. In this role, you'll be instrumental in developing, maintaining, and scaling our cloud infrastructure on Amazon Web Services (AWS). Your expertise will be key in enabling our machine learning teams to deploy, manage, and monitor their models efficiently, all while building a robust and automated environment under minimal supervision. Top daily responsibilities: β€’ Building out terraform automations for AWS. β€’ Providing customer service for Data Scientists and AI Engineers. β€’ MLOps & DevOps for GitHub and AWS. Other responsibilities include: β€’ Infrastructure Management: Work with the platform/infrastructure teams to implement, to improve and to automate infrastructure as code (IaC) to ensure consistency and repeatability. β€’ CI/CD Pipeline Development: Build and maintain robust CI/CD pipelines for both application and machine learning model deployments. This includes automating the entire workflow from code commit to production deployment. β€’ MLOps Implementation: Collaborate with data scientists and machine learning engineers to create and optimize the MLOps lifecycle. This involves automating model training, versioning, serving, and monitoring in a production environment. β€’ Automation: Automate repetitive tasks using scripts and tools to streamline operations and improve efficiency. β€’ Security: Working closely with the security teams, ensure the security of our cloud environment by implementing best practices, managing access controls, and conducting regular security audits. β€’ Collaboration: Work closely with development, data science, and product teams to understand their needs and provide technical solutions that meet business goals. The successful candidate will meet the following qualifications: β€’ Degree from an accredited college in computer science or related industry experience is required. β€’ 8+ years of professional DevOps experience is required. β€’ 2+ years of professional MLOps experience is required. β€’ 5+ years of strong expertise in the AWS ecosystem (e.g., EC2, S3, RDS, Lambda, SageMaker, EKS) is required. β€’ Hands-on experience with Terraform for building and managing infrastructure as code (IaC) is required. β€’ Solid understanding of MLOps principles and the challenges of deploying machine learning models at scale is required. β€’ 8+ years of professional experience building and managing CI/CD pipelines is required. β€’ Experience with containerization technologies (Docker, Kubernetes) is required. β€’ Strong communication skills and ability to work effectively in a team environment is required. β€’ 5+ years of professional experience with GitHub or similar code repositories is required. β€’ Strong knowledge of DevOps automations in the AWS ecosystem is required. β€’ Knowledge of scripting YAML, JSON, Shell, Bash, and Python is required. β€’ Hands-on experience with building and managing security as code (SaC) is preferred. β€’ Understanding basic networking principles between AWS and on-premises networks is preferred.