Responsibilities
- Design machine learning deployment, monitoring pipelines and engineering infrastructure to support enterprise ML systems at scale.
- Take offline models built by data scientists and turn them into production machine learning systems.
- 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 client ML systems.
- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
- Support model development with an emphasis on auditability, versioning, and data security.
- Facilitate the development and deployment of proof‑of‑concept machine learning systems.
- Communicate with clients to build requirements and track progress.
Qualifications & Skills
- 5‑8 years in cloud application development/administration with at least 4 years in AWS, Terraform, Jenkins, CloudFormation or similar IaC.
- 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, automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting, etc.).
- Strong hands‑on technical skills in automation, infrastructure as code, logging, monitoring and observability, infrastructure configuration, scripting languages and applications.
- Experience working in cloud ecosystem—building and deploying workloads on AWS.
- Associate certification (preferable) in AWS Development and/or Architect or any cloud related certification (Terraform/Chef).
- Understanding of AI, ML & Generative AI domain an added advantage.
- Ability to analyze escalations, prioritize, identify owners, track and facilitate blockers.
- Good understanding and knowledge of Chef / Python / Go and cloud networking.
- Essential security principles and processes.
- Excellent communication and interpersonal skills (verbal and written), ability to work effectively with a remote and multicultural team, following a collaborative and supportive approach.
- Strong analytical and organizational skills.
Hybrid work model. Broadridge is committed to fostering a collaborative, inclusive and healthy environment that promotes flexibility and accountability.