IT Job – MLOps Engineer/ 5-7 Years / Remote-Pan India

ISOURCE SERVICES; India; Remote; INR 1,200,000 - 1,500,000; Full time

Job summary

A technology company is hiring for the position of MLOps Engineer, focusing on the development and deployment of Machine Learning pipelines. The role requires strong programming skills in Python and familiarity with AWS services. Responsibilities include deploying ML models, optimizing model performance, and supporting observability tools. This is a remote position available across India.

Qualifications

• Strong programming skills in Python, with experience in pandas, SQL, and ML frameworks.
• Familiarity with AWS services such as Lambda, Glue, CloudWatch, and Bedrock.
• Experience with container workflows (Docker) and model lifecycle management.
• Foundational knowledge of observability practices and model deployment fundamentals.
• Interest or experience in supporting AI systems used by developers or analysts.
• Strong communication and documentation skills with a collaborative team mindset.
• Ability to assume ownership of assignments and consistently meet deadlines.

Responsibilities

• Deploy and maintain ML and GenAI models using AWS services.
• Apply prompt engineering techniques to optimize GenAI model performance.
• Assist in building and maintaining internal model-serving platforms.
• Implement containerized services using Docker and deploy them to AWS.
• Write Infrastructure-as-Code (IaC) using Terraform.
• Participate in unit and end-to-end testing of ML pipelines.
• Support model monitoring and health tracking using AWS CloudWatch.

Job description

Overview

IT Job – MLOps Engineer/ 5-7 Years / Remote-Pan India

iSource Services is Hiring for the position of MLOps Engineer.
Interested? Send us your updated CV/resume at: [e-mail]

About the Role

The ML Ops Engineer plays a critical role in the development, automation, and deployment of Machine Learning (ML) and Generative AI (GenAI) pipelines across AWS cloud environments. This hands-on role emphasizes building reproducible workflows, integrating observability tools, and enabling efficient, scalable model delivery. The position supports AI systems deployed in banking environments, where resilience and reliability are paramount.

Responsibilities

• Deploy and maintain ML and GenAI models using AWS services, Fargate, and Bedrock.
• Apply prompt engineering techniques to optimize GenAI model performance and reliability.
• Experience with Retrieval-Augmented Generation (RAG) applications is a plus.
• Assist in building and maintaining internal model-serving platforms to support development teams.
• Implement containerized services using Docker and deploy them to AWS infrastructure.
• Write Infrastructure-as-Code (IaC) using Terraform to automate cloud resource provisioning (nice to have).
• Participate in unit and end-to-end testing of ML pipelines, services, and monitoring workflows.
• Support model monitoring and health tracking using AWS CloudWatch and internal observability tools.

Qualifications

• Strong programming skills in Python, with experience in pandas, SQL, and ML frameworks (e.g., scikit-learn).
• Familiarity with AWS services such as Lambda, Glue, CloudWatch, and Bedrock.
• Experience with container workflows (Docker) and model lifecycle management.
• Foundational knowledge of observability practices and model deployment fundamentals.
• Interest or experience in supporting AI systems used by developers or analysts.
• Strong communication and documentation skills with a collaborative team mindset.
• Ability to assume ownership of assignments and consistently meet deadlines.

Contact

Interested candidates should send their CV/resume to [e-mail].