Responsibilities: 

• 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. 
• 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: 

• 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). 
• 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 cloud, preferably AWS. 
• Associate Certification (preferable) in AWS Development and/or Architect or any cloud related certification (Terraform/chef). 
• Understanding of AI, ML & Generative AI domain will be an added advantage as the team is focused on creating AIML capabilities for the organization. 
• 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, always following a collaborative and supportive approach. 
• Strong Analytical and organizational skills - ability to understand the design documents and communicate implementations 
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