Advisor IT Systems - AI/ML Ops

Key Responsibilities

• Design, build, and maintain MLOps pipelines and platforms for model training, deployment, monitoring, and retraining using AWS.
• Operationalize ML models for upstream use cases (e.g., production optimization, subsurface modeling, drilling analytics).
• Implement CI/CD, model versioning, experiment tracking, and performance monitoring.
• Collaborate with data scientists, data engineers, and domain experts to move models from development to production.
• Ensure reliability, observability, governance, and compliance of ML systems.
• Troubleshoot production issues related to data, models, and infrastructure.

Required Qualifications

• 5+ years of experience in data engineering, software engineering, MLOps, or AI Ops.
• Good grasp of software architecture principles and systems design.
• Strong proficiency in Python for production-grade ML workflows.
• Hands-on experience with AWS (e.g., S3, EC2, EKS/ECS, SageMaker, Lambda, CloudWatch).
• Experience deploying and supporting ML models in production environments.
• Familiarity with CI/CD tools, Docker, and Kubernetes.
• Understanding of ML lifecycle management, model monitoring, and data drift.

Preferred Qualifications

• Experience supporting analytics or ML solutions in upstream Oil & Gas or energy.
• Knowledge of time-series, forecasting, or physics-informed ML workloads.
• Experience with infrastructure-as-code (Terraform, CloudFormation).