Role & responsibilities

Machine Learning Engineering

Develop, train, evaluate, and deploy machine learning models at scale

Implement end-to-end ML pipelines from data ingestion to model serving

Work on model optimization, validation, and performance monitoring

Apply best practices for feature engineering and model lifecycle management

MLOps & Deployment

Build and maintain MLOps pipelines for CI/CD/CT (Continuous Training)

Automate model deployment, versioning, and monitoring

Implement experiment tracking and model registry (MLflow preferred)

Ensure model reproducibility, scalability, and governance

Python (OOPs) Development

Develop modular, reusable, and scalable code using object-oriented Python

Build robust backend services and ML utilities

Write clean, testable, and well-documented code

Databricks

Develop and optimize workflows on Azure Databricks

Work with PySpark for data processing and feature engineering

Manage notebooks, jobs, clusters, and Delta Lake pipelines

Optimize Spark jobs for performance and cost

Azure Cloud

Work with Azure services like Azure ML, Data Factory, Blob Storage, ADLS, Key Vault

Deploy models and pipelines using Azure DevOps / CI-CD pipelines

Implement secure, scalable,



and cost-productive cloud architectures

Data Engineering & Integration

Build and maintain data pipelines for ML workflows

Integrate models with APIs and downstream applications

Work with large datasets (structured & unstructured)

Preferred candidate profile

Required Skills & Qualifications

Core Skills

35 years of experience in Machine Learning / MLOps

Strong proficiency in Python with OOP concepts (mandatory)

Hands-on experience with Databricks & PySpark

Solid experience with Azure cloud ecosystem

Technical Skills

Experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch)

Hands-on with MLflow (experiment tracking & model registry)

Knowledge of CI/CD tools (Azure DevOps, Jenkins, GitHub Actions)

Strong understanding of data structures, algorithms, and system design basics

Experience with REST APIs and microservices

Preferred Skills

Exposure to feature stores and model monitoring tools

Knowledge of Docker & Kubernetes

Familiarity with Delta Lake, data lakes, and warehouse architectures

Experience with streaming (Kafka/Event Hub)

Understanding of data governance and security best practices

📌 MLE/MLOps, OOPs Python(Deployment and Monitoring)- @infosys (Telangana)
🏢 Infosys
📍 Telangana