AI/ML Engineer_MS

Role Overview

We are seeking an experienced AI/ML Engineer (4–6 years) with strong hands-on expertise in end-to-end machine learning, GenAI solution development, data engineering, and cloud-native deployment. The role involves building scalable AI systems, designing LLM-based applications, and integrating enterprise-grade MLOps pipelines across any one of Azure, GCP, and AWS environments.

Responsibilities

• Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks.
• Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash.
• Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Work with cross-functional teams to translate business needs into AI-driven outcomes.
• Deploy workloads using Azure App Service, Cloud Run, Azure Bot Service, Dialogflow, and other cloud-native platforms.
• Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining.
• Build and optimize ETL/ELT pipelines using Azure Data Factory, BigQuery, Databricks, and other data engineering tools.
• Create dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot.
• Ensure scalable, secure, and cost-optimized deployment across Azure/GCP/AWS environments.

Requirements

• Bachelor’s/Master’s degree in Computer Science, Engineering, or related field.
• 4–6 Years of relevant experience.
• Advanced Python and strong SQL skills.
• Experience with LangChain, LangGraph, and RAG architectures.
• Proficiency in cloud platforms like Azure, GCP, or AWS.
• Knowledge of Docker and CI/CD pipelines.

Skills

• Python
• LangChain
• Azure
• SQL
• MLOps