Job
Description
? ?Job Description ?Key Responsibilities End-to-End GenAI Development o Design and build GenAI applications using LLMs (e. g. , LLaMA, Mistral, GPT-J, Falcon, Claude, etc. ) o Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases like FAISS, ChromaDB, or Weaviate o Create and tune prompt templates, guardrails, and output parsers using tools like LangChain, Haystack, or LlamaIndex Agentic AI Autonomy o Develop AI agents that use planning, memory, tools, and self-reflection (e. g. , using AutoGen, CrewAI, or LangGraph) o Build task-oriented chains with autonomous behaviors for decision-making and workflow automation Model Training Fine-Tuning o Perform SFT on open-source models using libraries like HuggingFace Transformers, PEFT, LoRA, or QLoRA o Evaluate model performance using GenAI metrics and frameworks (e. g. , DeepEval, TruLens) ML System Integration o Use ML libraries like Scikit-learn, TensorFlow, PyTorch, and XGBoost to integrate traditional ML pipelines alongside GenAI components o Develop APIs and microservices (using FastAPI, Flask) to expose GenAI/ML services Security, Observability Control
