Description

You will manage and automate machine learning infrastructure and production pipelines across cloud environments.

This role is on-site.

Responsibilities

• Automate ML pipelines using MLflow, Kubeflow, or Airflow.
• Manage ML workloads on AWS and Azure.
• Implement CI/CD principles and containerization strategies.
• Deploy monitoring and alerting systems for ML models using Prometheus or Grafana.

Required Skills

• 8+ years of experience in MLOps, DevOps, data engineering, or ML infrastructure.
• Proficiency with AWS and Azure cloud platforms.
• Strong experience with SQL.
• Hands-on expertise with Docker and Kubernetes.
• Proven ability to build automated ML pipelines.
• Deep understanding of CI/CD workflows.
• Experience with monitoring tools like Prometheus and Grafana.
• Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent experience.
• Must be located in the EST time zone.

Preferred Skills

• Travel to Pennsylvania, NYC, or Toronto for initial project onboarding and monthly follow-ups.

Key Skills

Education

Bachelor's degree in Computer Science