Ml Ops & Observability Engineer

Pfizer

Budapest, Hungary
Hybrid
8+ years ml engineering experience
3+ years people leadership
Aws or azure cloud environments
Pfizer is seeking an MLOps & Observability Engineer to lead the design and implementation of MLOps platforms, focusing on model operations and observability. The ideal candidate will have over eight years of experience in ML engineering and a strong background in cloud environments, particularly AWS and Azure

Job Summary

  • This role involves leading the design and operation of MLOps platforms to support model development, deployment, and lifecycle management across Pfizer's research and manufacturing functions.
  • The engineer will own end-to-end observability for ML systems, implementing tooling like OpenTelemetry and Prometheus to track model performance, data drift, and pipeline health.
  • Candidates must have strong hands-on experience operationalizing ML systems in AWS or Azure while ensuring secure, compliant, and scalable infrastructure through DevSecOps practices.

Matching Summary

Match Score: 85

Pfizer is seeking an MLOps & Observability Engineer to lead the design and implementation of MLOps platforms, focusing on model operations and observability. The ideal candidate will have over eight years of experience in ML engineering and a strong background in cloud environments, particularly AWS and Azure.

Skills & Requirements

Must-have

  • 8+ years ML engineering experience
  • 3+ years people leadership
  • AWS or Azure cloud environments
  • OpenTelemetry Prometheus Grafana ELK
  • CI/CD for ML workloads
  • Model validation and regression testing
  • DevSecOps secure SDLC

Nice-to-have

  • Master's degree in CS or Data Science
  • MLflow Kubeflow feature stores
  • Data drift detection expertise
  • Responsible AI governance background
  • AWS/Azure Professional certifications
  • Kubernetes CKA CKAD certification

Key Requirements

  • 8+ years ML engineering or platform engineering
  • 3+ years people leadership experience
  • Strong Python Bash SQL proficiency
  • Experience with containerized cloud-native runtimes
  • Proven expertise in ML testing and validation
  • Background in secure SDLC for AI/ML

Work Rights

Not specified

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