Cloud DevOps Engineer

Cloud DevOps Engineer focuses on design the ml deploy, monitoring pipelines and engineering infrastructure to support enterprise machine learning systems at scale.

What the role involves

• Design the ML deploy, monitoring pipelines and engineering infrastructure to support enterprise machine learning systems at scale.
• Take offline models data scientists build and turn them into a real machine learning production system.
• Develop and deploy scalable tools and services to handle machine learning training and inference.
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems.
• Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
• Supporting model development, with an emphasis on auditability, versioning, and data security.

Skills and requirements

• Over all 5-8 years in cloud application development/Administration with at least 4 years of experience in AWS & Terraform, Jenkins, Cloudformation or any other IAAC.
• Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools.
• Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting etc).
• Experience working in Cloud ecosystem- building and deploying workloads on cloud, preferably AWS.

Confirmed role details

• This role is considered hybrid.
• As part of the recruiting process, Broadridge may use technology, including artificial intelligence (AI)-based tools, to help review and evaluate applications.

Candidate fit

• automation discipline, troubleshooting, documentation, and confidence with operational reliability