AI/ML Engineer

Key Responsibilities


Design, develop, train, and deploy Machine Learning and AI models.
Integrate LLMs with Knowledge Graphs, vector databases, and enterprise systems.
Fine-tune prompts, response handling, and context management for conversational workflows.
Develop AI pipelines using Python and ML frameworks.
Build and optimize embeddings, vector search, and similarity search mechanisms using FAISS or equivalent technologies.
Collaborate with product, IAM, DevOps, and engineering teams for AI feature integration.
Monitor model performance, hallucination handling, drift detection, and response quality.
Collaborate with product, engineering, and business teams to define AI use cases.
Develop REST APIs and integrate AI models into applications and services.
Support MLOps, CI/CD pipelines, and cloud deployment activities.
Document AI models, workflows, and technical designs.


Mandatory Skills


5–8 years of experience in AI/ML engineering or GenAI application development.
Strong programming skills in Python.
Experience with AI/ML frameworks and libraries:TensorFlow and PyTorch
Experience with Generative AI and LLM technologies: Amazon Bedrock, OpenAI Platform, LangChain and LangGraph
Experience in NLP, embeddings, semantic search, and RAG architectures.
Experience with graph databases:Neo4j
Knowledge of data processing and model evaluation techniques.
Experience with SQL and NoSQL databases.