Senior AI Engineer: Build Production-Grade AI Systems

Covestro

Pittsburgh (Allegheny County)

On-site

USD 140,000 - 180,000

Full time

14 days+
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Job summary

Covestro in the United States seeks a Senior AI Engineer to design, develop, and deploy enterprise AI solutions. This role bridges theory and production, ensuring scalable, reliable systems that deliver business value.

You will collaborate with data science teams to turn innovative concepts into robust production AI, and design comprehensive MLOps/AIOps pipelines for lifecycle management. Responsibilities include cloud/edge deployments, microservices for AI, monitoring drift, and enabling

Qualifications

  • Bachelor's or higher in CS/SE or related field
  • 7+ years' experience in AI/ML engineering in production
  • Experience with modern AI frameworks

Responsibilities

  • Engineer and deploy AI/ML models into production environments
  • Design and implement MLOps and AIOps pipelines for model lifecycle management
  • Create monitoring systems to detect model drift and retraining needs
  • Architect scalable AI solutions leveraging cloud and edge computing
  • Develop and maintain microservice architectures supporting AI deployments
  • Collaborate with data scientists to optimize model performance
  • Align AI solutions with business needs
  • Drive business value by integrating AI into core processes

Skills

AI/ML engineering
Python programming
Problem solving
Communication
Adaptability
Travel willingness

Education

Bachelor's degree in Computer Science, Software Engineering, or related field
Master's degree in Computer Science, Software Engineering, or related field
PhD in related field

Tools

Docker
Kubernetes

Job description

Covestro in the United States seeks a Senior AI Engineer to design, develop, and deploy enterprise AI solutions. This role bridges theory and production, ensuring scalable, reliable systems that deliver business value.

You will collaborate with data science teams to turn innovative concepts into robust production AI, and design comprehensive MLOps/AIOps pipelines for lifecycle management. Responsibilities include cloud/edge deployments, microservices for AI, monitoring drift, and enabling

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