Wood Mackenzie is seeking a Principal MLOps Engineer to design and optimize their machine learning infrastructure. The ideal candidate will have extensive experience in MLOps and a strong background in software engineering, DevOps, or data engineering
Job Summary
Design, build, and maintain highly scalable, robust, and secure machine learning infrastructure and platforms across the entire organization.
Establish and optimize automated CI/CD/CT pipelines for machine learning models, ensuring seamless transitions from research to production.
Implement enterprise-grade monitoring, alerting, and logging for model performance, data drift, concept drift, and system health.
Matching Summary
Match Score: 85
Wood Mackenzie is seeking a Principal MLOps Engineer to design and optimize their machine learning infrastructure. The ideal candidate will have extensive experience in MLOps and a strong background in software engineering, DevOps, or data engineering.
Skills & Requirements
Must-have
MLOps vision and roadmap
Automated CI/CD/CT pipelines
Complex model deployment (LLMs, deep learning)
Enterprise-grade monitoring and alerting
AWS managed ML/AI services (SageMaker, Bedrock)
Kubernetes, Docker, MLFlow
Python, C++, Java
GitHub Actions, Terraform
Nice-to-have
Bridging research and production
Mentoring data scientists
Setting engineering standards
Cross-functional collaboration
Key Requirements
Extensive experience in MLOps, ML infrastructure, or deploying ML models at scale
Deep, hands-on expertise with AWS
Advanced proficiency with Kubernetes, Docker, MLFlow
Strong software development skills in Python
Mastery of automation tools and IaC frameworks
Strong understanding of ML and deep learning frameworks
Demonstrated ability to lead complex technical initiatives