ML Ops Engineer

Role and Designation : ML Ops Engineer

Number of Positions : 1

Desired Experience : 3 to 6 years 

We are seeking an ML Ops Engineer to operationalize and manage the lifecycle of machine learning models, especially those built using Azure and Databricks. You will be key in deploying, monitoring, and optimizing models across multiple business use cases.

Key Responsibilities:

Maintain, optimize, and scale recommendation engines

Continuously improve recommendation models

Enhance and maintain graph-based models

Develop and evolve an enterprise-grade knowledge graph

Ensure explainability, reproducibility, and scalability

Collaborate with product, marketing, and engineering teams

Required Skills:

Programming Languages

Big Data Technologies

Data Formats & Storage

Cloud Platforms

Graph Technologies

ML/AI

Monitoring & Logging

•   Advanced knowledge in retrieval augmented generation systems
•   Expertise in vector databases and embedding strategies
•   Proficiency in context retrieval algorithms
•   Experience designing evaluation frameworks for AI systems
•   Strong background in segmented execution frameworks
•   Skills in distributed computing solutions for AI workloads
•   Knowledge of intelligent task routing systems
•   Ability to create orchestration layers for AI workflows
•   Experience integrating AI capabilities into enterprise applications
•   Proficiency in API design and implementation for AI systems
•  Knowledge of CI/CD pipelines for AI components Nice to Have
•   Skills in monitoring and observability solutions
•   Experience with AI-powered forecasting and optimization
•   Expertise in intelligent document processing
•   Knowledge of AI assistant development
•   Proficiency in advanced analytics and trend identification