Huntington's MLOps Automation Engineering Senior Lead will lead a team responsible for building and deploying MLOps Automation for some of Huntington’s most valuable and most challenging data-driven projects.
Requirements
- 10+ years of experience with one or more coding languages (e.g., JavaScript, C++, Python, Java), CI/CD tools (e.g., Jenkins, Artifactory, CircleCI, Ansible), and development platforms (e.g., AWS, Azure, Docker, Kubernetes)
- Experience developing CI/CD workflows and tools
- Strong automation scripting skills
- Experience in configuration management, test-driven development, and release management.
- Strong analytical and troubleshooting skills.
- Strong understanding of DataOps and ModelOps principles
- Ability to investigate and analyze information, and to draw conclusions
Responsibilities
- Streamline the data, analytics, and model development lifecycle by identifying pain points and productivity barriers and determining ways to resolve them through automation.
- Understand the current process and technical complexities of developing and deploying data pipelines and model builds and develop automation solutions to improve and extend the existing process to become an unattended delivery pipeline.
- Collaborate closely with product development, architecture, data engineering and testing teams to understand their current build and release processes and make recommendations for improvement through the automation of various tasks.
- Develop and continuously improve automation solutions to enable teams to build and deploy quality data and code efficiently and consistently.
- Build automated testing solutions in support of quality management objectives to reduce manual effort.
- Build automated environment provisioning solutions in response to changes in processing demand.
- Build automated feedback mechanisms to monitor the performance of models in production.
Other
- Helps set the strategy and tone for MLOps Automating Engineering strategy and vision for the future.
- Partner with cross-functional stakeholders, including development, operations, quality assurance and security, to streamline processes.
- Work closely with cross-functional stakeholders to analyze and troubleshoot complex production issues.
- Prepare and present design and implementation documentation to multiple stakeholders.
- Promote automation across the data management and analytics delivery organization.
