Highlights

Skilled in bridging the gap between Data Science, Machine Learning, and DevOps by building scalable MLOps pipelines, implementing CI/CD processes, managing model lifecycle operations, and ensuring reliable model performance. Experienced in developing secure, automated, and scalable infrastructure that enables efficient delivery of AI and machine learning solutions.

Numbers & Facts

LocationCincinnati, OH

Description

Role: MLOps Engineer

Location: Cincinnati, OH
Duration: 6 months

Requirements:
  • MLOps Engineer with experience designing, deploying, automating, and monitoring machine learning solutions in production environments.
  • Skilled in bridging the gap between Data Science, Machine Learning, and DevOps by building scalable MLOps pipelines, implementing CI/CD processes, managing model lifecycle operations, and ensuring reliable model performance.
  • Proficient in Python, MLflow, Docker, Kubernetes, cloud platforms, and machine learning deployment frameworks.
  • Experienced in developing secure, automated, and scalable infrastructure that enables efficient delivery of AI and machine learning solutions.
Role Descriptions: ML Engineer

Skills: Digital : Machine Learning
Experience Required: 8-10

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