Wood Mackenzie is redefining the energy landscape by fusing proprietary data with Synoptic AI to deliver interconnected value chain views
Job Summary
Wood Mackenzie is redefining the energy landscape by fusing proprietary data with Synoptic AI to deliver interconnected value chain views.
The Principal MLOps Engineer will drive the architectural vision for enterprise machine learning infrastructure while bridging research and production.
This role requires leading technical strategy for end-to-end ML lifecycles, including automated pipelines, model serving optimization, and rigorous observability.
Matching Summary
Wood Mackenzie is redefining the energy landscape by fusing proprietary data with Synoptic AI to deliver interconnected value chain views.
Skills & Requirements
Must-have
AWS SageMaker and Bedrock expertise
Kubernetes and Docker orchestration
Python C++ or Java programming
MLFlow and CI/CD pipeline mastery
Terraform and Infrastructure as Code
PyTorch TensorFlow optimization skills
Enterprise AI governance implementation
Nice-to-have
Mentoring data scientists effectively
Leading complex technical initiatives
Cross-functional stakeholder management
Fostering engineering excellence culture
Deep learning model deployment experience
Key Requirements
Extensive software engineering or DevOps experience
Proven track record in MLOps and ML infrastructure
Demonstrated ability to lead multi-quarter technical initiatives