MLOps / AI Ops Engineer 
 (PRIORITY)  TOP Communication

As an MLOps / AI Ops Engineer, you will be responsible for deploying, monitoring, and supporting machine learning models in a production environment. You will work with Amazon SageMaker, AWS MLOps, and other relevant technologies to ensure the successful deployment and operation of machine learning systems. This role requires a strong background in machine learning operations and artificial intelligence, as well as proficiency in Python and containerization technologies like Docker and Kubernetes.

Responsibilities:

• Deploy and manage machine learning models using AWS SageMaker
• Implement production ML deployment, monitoring, and support with AWS MLOps
• Develop automation scripts and tools using Python
• Utilize Docker and Kubernetes for containerization and orchestration
• Set up and maintain CI/CD pipelines for machine learning workflows
• Monitor and manage the lifecycle of machine learning models
• Collaborate with cross-functional teams to ensure effective communication and project delivery

Requirements:

• Must-Haves:
  • AWS SageMaker – strong hands-on experience
  • AWS MLOps – production ML deployment, monitoring & support
  • Python – strong development/automation skills
  • Docker & Kubernetes (EKS/ECS)
  • CI/CD pipelines
  • ML model monitoring, observability & lifecycle management
  • Strong communication skills
• AWS Stack: SageMaker, S3, EC2, EKS/ECS, Lambda, CloudWatch
• Nice to Have: Terraform/CloudFormation, data drift detection, forecasting/time-series analytics, Oil & Gas/Upstream experience
• Candidate Requirements:
  • A Players: Must already be in Houston, TX
  • B Players: Must be in Texas and able to relocate to Houston at their own expense before Day 1
  • Must be onsite Tuesday–Thursday at Greenway Plaza
  • 5 years MLOps / AI Ops / Data Engineering / Software Engineering experience
  • Excellent communication is critical