Lead Machine Learning Operations Engineer
3 weeks ago
About the Role
We are seeking a highly skilled Lead Machine Learning Ops 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.
Responsibilities
- Develop and maintain automated build and deployment processes to enable continuous delivery of software releases, enhancing our 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 our existing DevOps practices to improve the overall AI/ML application development lifecycle, ensuring 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, or Master's Degree in a relevant field and 5+ years of experience.
- Expertise in code versioning tools, such as GitLab, GitHub, Azure DevOps, Bitbucket, etc., with a strong familiarity with branch-level code repository management.
- Experience deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP), with a preference for Databricks and AWS.
- Proficiency in GitHub Actions to automate testing and deployment of data and ML workloads from CI/CD providers to Databricks.
- Strong knowledge of infrastructure automation tools such as Terraform, Ansible, CloudFormation, etc.
- Experience with data processing frameworks/tools/platforms 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.
What We Offer
We offer a comprehensive benefits package, including medical, dental, and vision insurance, wellness programs, retirement plans, and generous paid leave. Our Total Rewards package underscores our commitment to recognizing your contributions and providing a competitive and fair compensation structure.
About The Friedkin Group
The Friedkin Group is committed to ensuring equal employment opportunities and providing reasonable accommodations to individuals with disabilities. If you have a disability and would like to request an accommodation, please contact us at TalentAcquisition@friedkin.com. We celebrate diversity and are committed to creating an inclusive environment for all associates.
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