Senior ML Ops Engineer

Paradigm

  • Irving, Texas
  • 10 days ago

    Highlights

    We are powered by our parent company, Builders FirstSource (NYSE: BLDR): a Fortune 300 company with over $23 billion in revenue and more than 29,000 employees across 550+ locations, BFS is redefining construction through data, digital infrastructure, and AI-powered innovation. · Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining.

    Numbers & Facts

    LocationIrving, Texas
    Websitehttps://myparadigm.com/

    Description

    Paradigm is a software company transforming the way that the residential, construction & building product industries operate across the globe. We are looking for a SeniorML Ops Engineer to be part of revolutionizing these industries. We are building the future with modern software engineering, agent-assisted systems, and mobile-first experiences. We are powered by our parent company, Builders FirstSource (NYSE: BLDR): a Fortune 300 company with over $23 billion in revenue and more than 29,000 employees across 550+ locations, BFS is redefining construction through data, digital infrastructure, and AI-powered innovation.

    What You Will Do:

    · Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining.

    · Develop and optimize automated ML deployment pipelines, ensuring reliable, reproducible, and efficient model delivery to production environments.

    · Deploy and support machine learning models and AI solutions in production, maintaining best practices for scalability, reliability, security, and operational excellence.

    · Implement and maintain model registries, experiment tracking, versioning, and governance practices to support consistent model lifecycle management.

    · Build and support containerized ML workloads and deployment workflows using technologies such as Docker and Kubernetes.

    · Develop monitoring, observability, and alerting capabilities for machine learning systems, including model performance tracking, drift detection, and data quality monitoring.

    · Collaborate with Machine Learning Engineers, Data Scientists, Software Engineers, and Infrastructure teams to operationalize ML solutions and improve deployment efficiency.

    · Implement and maintain IaC patterns using Terraform.

    · Troubleshoot and resolve complex technical challenges related to model deployment, ML infrastructure, and production operations.

    · Provide guidance and mentorship to other engineers.

    What You Need to Succeed:

    · Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence or related field or equivalent experience.

    · 4+ years of professional experience in software engineering, machine learning engineering, MLOps, platform engineering, DevOps, or a related technical discipline.

    · Strong understanding of the machine learning lifecycle, including model training, validation, deployment, monitoring, and retraining.

    · Experience building and maintaining automated machine learning pipelines and CI/CD workflows.

    · Experience with MLOps platforms and tools such as MLflow, Kubeflow, Azure Machine Learning, Databricks, or similar technologies.

    · Experience in Python programming, ML Framework and Agentic AI. Implemented model monitoring, experiment tracking, model versioning, and governance practices.

    · Experience working with cloud-based machine learning solutions, preferably within Azure.

    · Ability to independently solve complex technical challenges, make sound decisions with minimal guidance, and drive work to completion.

    Ready to Join? Apply now at myparadigm.com/careers/

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