This role involves leading the design and operation of MLOps platforms to support model development, deployment, and lifecycle management across Pfizer's functions
Job Summary
This role involves leading the design and operation of MLOps platforms to support model development, deployment, and lifecycle management across Pfizer's functions.
You will own end-to-end observability for ML systems, utilizing tools like OpenTelemetry, Prometheus, and Grafana to monitor performance, data quality, and pipeline health.
The position requires partnering with infrastructure and DataOps teams to ensure ML workloads run on secure, scalable, and cost-effective cloud-native environments.
Matching Summary
This role involves leading the design and operation of MLOps platforms to support model development, deployment, and lifecycle management across Pfizer's functions.
Skills & Requirements
Must-have
8+ years ML engineering experience
3+ years people leadership
AWS or Azure cloud environments
OpenTelemetry Prometheus Grafana ELK
CI/CD pipelines for ML workloads
Model registry and experiment tracking
DevSecOps secure SDLC for AI
Nice-to-have
Master's degree in CS or Data Science
MLflow Kubeflow feature stores experience
Data drift detection expertise
Responsible AI governance background
AWS/Azure Professional certifications
Kubernetes CKA CKAD certification
Cloud security certifications
Key Requirements
8+ years ML engineering or platform engineering experience
3+ years people leadership experience
Strong hands-on AWS or Azure operational experience
Proficiency in Python Bash SQL scripting
Experience with containerized cloud-native ML runtimes
Demonstrated DevSecOps implementation for AI/ML systems