Job Opening For Agentic AIOps/MLOps Lead - Technology

Role Summary

We are seeking a highly motivated MLOps Engineer with experience in Machine Learning, Generative AI, Cloud Platforms, and DevOps practices. The ideal candidate will be responsible for building, deploying, automating, and monitoring machine learning models and AI applications in production environments while ensuring scalability, reliability, and operational efficiency.

Key Responsibilities

• Design, build, and maintain end-to-end MLOps pipelines for machine learning and AI solutions.

• Deploy and manage ML models in production using cloud-native technologies and containerized environments.

• Develop and maintain high-performance RESTful APIs and microservices for ML model serving.

• Implement CI/CD pipelines for automated model training, testing, deployment, and monitoring.

• Work closely with Data Scientists and AI Engineers to operationalize machine learning solutions.

• Build and manage feature stores, model registries, experiment tracking, and monitoring frameworks.

• Develop and optimize RAG (Retrieval-Augmented Generation) and LLM-based applications.

• Ensure model reliability, scalability, security, and performance in production environments.

• Monitor model drift, data quality, and system performance to drive continuous improvements.

• Implement infrastructure-as-code and automation for cloud-based ML deployments.

Required Skills

Machine Learning & AI

• Strong understanding of the Machine Learning lifecycle.

• Experience with Machine Learning, Deep Learning, NLP, and Generative AI solutions.

• Knowledge of model training, validation, deployment, and monitoring.

• Experience working with OpenAI and Large Language Models (LLMs).

MLOps & Deployment

• Hands-on experience with:

  • MLflow

  • Feature Stores

  • Pinecone

  • Tecton

  • Model Monitoring Tools

• Experience in model versioning, experiment tracking, and deployment automation.

• Strong understanding of CI/CD practices for ML workloads.

Cloud & Infrastructure

• Experience with AWS and/or Azure cloud platforms.

• Hands-on experience with:

  • AWS SageMaker

  • S3

  • Kinesis

  • EKS

  • CloudFormation

  • Azure Machine Learning

  • Databricks

Programming & Frameworks

• Strong programming skills in:

  • Python

  • SQL

  • Java/Scala (preferred)

• Experience with:

  • TensorFlow

  • PyTorch

  • Scikit-learn

  • Keras

  • Apache Spark

Containerization & Orchestration

• Docker

• Kubernetes

• Git

• CI/CD Tools

• Infrastructure Automation

Data Engineering

• ETL Pipelines

• Data Preprocessing

• Feature Engineering

• Data Transformation

• Distributed Computing

Preferred Skills

• Experience with AIOps and IT Operations Automation.

• Experience with Vector Databases and RAG architectures.

• Knowledge of Kafka, Redis, and Event-Driven Architectures.

• Exposure to enterprise-scale AI/ML deployments.

• Cloud certifications in AWS or Azure.

Soft Skills

• Strong analytical and problem-solving skills.

• Excellent communication and stakeholder management.

• Ability to work in cross-functional teams.

• Continuous learning mindset and adaptability.

Experience Required

3-6 Years of experience in MLOps, Machine Learning Engineering, AI Platform Engineering, or related domains.

Location

Bangalore / Salem