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Lead Machine Learning Operations Engineer

2 months ago

Rosenberg, Texas, United States The Friedkin Group Full time
About the Role

We are seeking a highly skilled Lead Machine Learning Operations Engineer to join our Corporate Data & Analytics Team. As a key member of our team, you will play a pivotal role in implementing DevOps and ML Ops practices to support AI/ML application enablement across The Friedkin Group of companies.

Key Responsibilities
  • Develop automated build and deployment processes to enable continuous delivery of software releases, enhance the existing CI/CD pipelines for AI/ML application development and deployment.
  • Collaborate with data scientists, data engineers, data analysts, software engineers, IT specialists, and stakeholders to accelerate deployment of AI applications via CI/CD pipelines and maintain the SLAs of those applications at the centralized platform.
  • Design, develop, and maintain infrastructure using infrastructure as code tools such as Terraform, Ansible, CloudFormation, etc.
  • Templatize existing Databricks CLI codes to manage Databricks platform as code for AI/ML data pipelines (batch processing, batch streaming, and streaming) and model serving endpoints.
  • Enhance the existing DevOps practices to improve the overall AI/ML application development lifecycle.
  • Work closely with cross-functional teams to ensure that applications are highly available and scalable.
  • Collaborate with development teams and cloud platform teams to ensure that infrastructure meets the requirements of the application.
  • Establish and maintain best practices for cloud security, compliance, and cost optimization.
Requirements
  • Bachelor's Degree in Computer Science, Computer Engineering, Information Technology, Software Engineering, or equivalent technical discipline and 10+ years of experience in software engineering with a strong background in DevOps and Infrastructure as Code, supporting Machine Learning and Data Science workloads preferred.
  • Master's Degree in Computer Science, Computer Engineering, Information Technology, Software Engineering, or equivalent technical discipline and 5+ years of experience in software engineering with a strong background in DevOps and Infrastructure as Code, supporting Machine Learning and Data Science workloads preferred.
  • Expertise on code versioning tools, such as GitLab, GitHub, Azure DevOps, Bitbucket, etc., GitHub preferred, familiar with branch-level code repository management.
  • Experience deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP). Databricks and AWS preferred.
  • Proficient with GitHub actions to automate testing and deployment of data and ML workloads from CI/CD provider to Databricks.
  • Strong knowledge of infrastructure automation tools such as Terraform, Ansible, CloudFormation, etc.
  • Experience with data processing frameworks/tools/platform such as Databricks, Apache Spark, Kafka, Flink, AWS cloud services for batch processing, batch streaming, and streaming.
  • Experience containerizing analytical models using Docker and Kubernetes or other container orchestration platforms.
  • Technical expertise across all deployment models on public cloud, private cloud, and on-premises infrastructure.
  • Experience in event-driven and microservice architectures for enterprise-level platform development.
  • Expertise in Linux and knowledge of networking and security concepts.
  • Effective communication skills and a sense of ownership and drive.
  • Capable of coaching/mentoring individuals and teams.
About The Friedkin Group

The Friedkin Group is committed to ensuring equal employment opportunities, including providing reasonable accommodations to individuals with disabilities. If you have a disability and would like to request an accommodation, please contact us at. We celebrate diversity and are committed to creating an inclusive environment for all associates.

We are seeking candidates legally authorized to work in the United States, without Sponsorship.