Advisor IT Systems - AI/ML Ops

CEU Carbon Engineering ULC; United States; On-site; USD 100,000 - 140,000; Full time

Job summary

CEU Carbon Engineering ULC is looking for a mid-career MLOps / AI Ops Engineer to enhance the deployment and management of machine learning solutions. This position emphasizes collaboration across data science, cloud engineering, and operations to maintain secure AI systems.

Applicants should possess over 5 years of experience, strong skills in Python, and hands-on knowledge of AWS services. The role involves designing MLOps pipelines and optimizing ML models in production.

Qualifications

• 5+ years of experience in data engineering, software engineering, MLOps, or AI Ops.
• Strong proficiency in Python for production-grade ML workflows.
• Hands-on experience with AWS services.

Responsibilities

• Design, build, and maintain MLOps pipelines and platforms using AWS.
• Operationalize ML models for production optimization and drilling analytics.
• Collaborate with data scientists and engineers to move models to production.

Skills

Data engineering

Software engineering

MLOps

AI Ops

Python

AWS

CI/CD

Docker

Kubernetes

Tools

AWS (e.g., S3, EC2, EKS/ECS, SageMaker, Lambda, CloudWatch)

Terraform

CloudFormation

Job description

Mid‑Career MLOps / AI Ops Engineer

We are seeking a mid‑career MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas operations. This role bridges data science, cloud engineering, and operations to ensure reliable, scalable, and secure AI systems in production.

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 such as production optimization, subsurface modeling, and 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).

Equal Employment Opportunity

All qualified applicants will receive consideration for employment without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.