AI/ML Engineer

AI/ML Engineer (5-8 years)

Key Responsibilities

• ML and GenAI solutions

• API-based AI applications

• 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.

• Azure App Service, Cloud Run

• MLOps workflows

• ETL/ELT pipelines

• 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.

Required Technical Skills

Programming & Languages

• Python (advanced), SQL (strong), HTML/CSS/JavaScript (working knowledge)

LLMs & GenAI

• LangChain, LangGraph

• Google ADK, Vertex AI, AWS Bedrock

• RAG architectures, embeddings, vector retrieval

• Prompt design, evaluation metrics, guardrails/security

• Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Document Intelligence

• Custom model development using GPT, LangChain, and relevant frameworks

• Prompt engineering, LogProbs handling, vector search integrations

Data Engineering & Platforms

• BigQuery, Azure Synapse, Azure Data Factory, Databricks

• Blob Storage, Cloud Storage, Document AI

• Strong understanding of ETL/ELT, feature engineering & data profiling

• Event-driven architecture and streaming systems for agentic workflows

• Data ingestion, transformation, and vector database management

• Ensuring data quality, lineage, governance, and observability

BI & Analytics

• Power BI, Tableau, Looker, ThoughtSpot, QuickSight

DevOps & MLOps

• Docker, CI/CD pipelines

• Model deployment & monitoring

• Vertex AI Agent Engine, model registry, experiment trackingQualifications

Educational qualification:

Bachelor s/Master s degree in Computer Science, Engineering, or related field.

Experience :

5-8 Years