Job Description & Summary: A career within Enterprise Architecture services, will provide you with the opportunity to bring our clients a competitive advantage through defining their technology objectives, assessing solution options, and devising architectural solutions that help them achieve both strategic goals and meet operational requirements. We help build software and design data platforms, manage large volumes of client data, develop compliance procedures for data management, and continually researching new technologies to drive innovation and sustainable change. 

Responsibilities: 

As a AWS DEVOPS MLOPs Engineer, you will be responsible for building and setting up new development tools and infrastructure utilizing knowledge in continuous integration, delivery, and deployment (CI/CD), Cloud technologies, Container Orchestration and Security. Your typical day will involve building and testing end-to-end CI/CD pipelines, ensuring that systems are safe against security threats, and utilizing your expertise in UNIX Shell Scripting. Operationalize ML models developed by scientists, moving them from prototypes to scalable, real-time production APIs. 
 

Mandatory skill sets: 

Pipeline Automation: Build and maintain CI/CD pipelines for machine learning workflows to enable rapid, automated deployment. 

Production Deployment: Operationalize ML models developed by scientists, moving them from prototypes to scalable, real-time production APIs (using Amazon SageMaker, EKS, Lambda). 

Monitoring & Governance: Implement monitoring systems to track model performance, data drift, and latency. 

Infrastructure Management: Provision and manage AWS infrastructure (S3, EC2, CloudFormation) tailored for ML training and inference. 

Collaboration: Work with data scientists to optimize models for production and with DevOps for infrastructure. 

Preferred skill sets: 

 GenAI/LLM Focus: In cutting-edge roles, establish robust pipelines for LLM fine-tuning and deployment (using tools like LangChain or Amazon Bedrock). 

Years of experience required:  

3+ yrs exp 

Education qualification: 

B.E. / B.Tech / MCA/ M.E/ M.TECH/ MBA/ PGDM. All qualifications should be in regular full-time mode with no extension of course duration due to backlogs