AI/ML

Key Responsibilities:
● Fine-tune and optimize LLMs such as LLaMA and OpenAI GPT using advanced prompt
engineering and parameter-efficient techniques (LoRA, quantization).
● Design and implement end-to-end RAG pipelines with vector search (FAISS, hybrid
retrieval, re-ranking).
● Build autonomous AI agents using LangChain and modern Agent Development Kits
(ADK), including tool-calling, memory management, and multi-agent orchestration.
● Develop and optimize ML/DL models using PyTorch and TensorFlow, including
multimodal architectures.
● Build scalable APIs using FastAPI/Flask and deploy AI systems on AWS/Azure.
● Implement guardrails, evaluation metrics, monitoring, and performance optimization for
production AI systems.
● Containerize and manage deployments using Docker and Git.
Required Qualifications:
● Strong proficiency in Python with solid understanding of Data Structures & Algorithms.
● Hands-on experience with PyTorch, TensorFlow, and Hugging Face Transformers.
● Experience building and fine-tuning LLMs (e.g., LLaMA, OpenAI GPT) including LoRA
and quantization techniques.
● Strong experience in designing RAG pipelines and implementing vector search (FAISS,
hybrid retrieval).
● Experience building AI agents with tool-calling, memory management, and orchestration
(LangChain/ADK)
● Experience developing APIs using FastAPI or Flask.
● Working knowledge of SQL/MySQL, Redis, and cloud deployment (AWS/Azure).
● Familiarity with Docker, Git, and production deployment practices

Tasks

Fine-tune and optimize LLMs such as LLaMA and OpenAI GPT using advanced prompt
engineering and parameter-efficient techniques (LoRA, quantization).
● Design and implement end-to-end RAG pipelines with vector search (FAISS, hybrid
retrieval, re-ranking).
● Build autonomous AI agents using LangChain and modern Agent Development Kits
(ADK), including tool-calling, memory management, and multi-agent orchestration.
● Develop and optimize ML/DL models using PyTorch and TensorFlow, including
multimodal architectures.
● Build scalable APIs using FastAPI/Flask and deploy AI systems on AWS/Azure.
● Implement guardrails, evaluation metrics, monitoring, and performance optimization for
production AI systems.
● Containerize and manage deployments using Docker and Git

Requirements

Strong proficiency in Python with solid understanding of Data Structures & Algorithms.
● Hands-on experience with PyTorch, TensorFlow, and Hugging Face Transformers.
● Experience building and fine-tuning LLMs (e.g., LLaMA, OpenAI GPT) including LoRA
and quantization techniques.
● Strong experience in designing RAG pipelines and implementing vector search (FAISS,
hybrid retrieval).
● Experience building AI agents with tool-calling, memory management, and orchestration
(LangChain/ADK)
● Experience developing APIs using FastAPI or Flask.
● Working knowledge of SQL/MySQL, Redis, and cloud deployment (AWS/Azure).
● Familiarity with Docker, Git, and production deployment practices.

Key Responsibilities:
● Fine-tune and optimize LLMs such as LLaMA and OpenAI GPT using advanced prompt
engineering and parameter-efficient techniques (LoRA, quantization).
● Design and implement end-to-end RAG pipelines with vector search (FAISS, hybrid
retrieval, re-ranking).
● Build autonomous AI agents using LangChain and modern Agent Development Kits
(ADK), including tool-calling, memory management, and multi-agent orchestration.
● Develop and optimize ML/DL models using PyTorch and TensorFlow, including
multimodal architectures.
● Build scalable APIs using FastAPI/Flask and deploy AI systems on AWS/Azure.
● Implement guardrails, evaluation metrics, monitoring, and performance optimization for
production AI systems.
● Containerize and manage deployments using Docker and Git.
Required Qualifications:
● Strong proficiency in Python with solid understanding of Data Structures & Algorithms.
● Hands-on experience with PyTorch, TensorFlow, and Hugging Face Transformers.
● Experience building and fine-tuning LLMs (e.g., LLaMA, OpenAI GPT) including LoRA
and quantization techniques.
● Strong experience in designing RAG pipelines and implementing vector search (FAISS,
hybrid retrieval).
● Experience building AI agents with tool-calling, memory management, and orchestration
(LangChain/ADK)
● Experience developing APIs using FastAPI or Flask.
● Working knowledge of SQL/MySQL, Redis, and cloud deployment (AWS/Azure).
● Familiarity with Docker, Git, and production deployment practices

Tasks

Fine-tune and optimize LLMs such as LLaMA and OpenAI GPT using advanced prompt
engineering and parameter-efficient techniques (LoRA, quantization).
● Design and implement end-to-end RAG pipelines with vector search (FAISS, hybrid
retrieval, re-ranking).
● Build autonomous AI agents using LangChain and modern Agent Development Kits
(ADK), including tool-calling, memory management, and multi-agent orchestration.
● Develop and optimize ML/DL models using PyTorch and TensorFlow, including
multimodal architectures.
● Build scalable APIs using FastAPI/Flask and deploy AI systems on AWS/Azure.
● Implement guardrails, evaluation metrics, monitoring, and performance optimization for
production AI systems.
● Containerize and manage deployments using Docker and Git

Requirements

Strong proficiency in Python with solid understanding of Data Structures & Algorithms.
● Hands-on experience with PyTorch, TensorFlow, and Hugging Face Transformers.
● Experience building and fine-tuning LLMs (e.g., LLaMA, OpenAI GPT) including LoRA
and quantization techniques.
● Strong experience in designing RAG pipelines and implementing vector search (FAISS,
hybrid retrieval).
● Experience building AI agents with tool-calling, memory management, and orchestration
(LangChain/ADK)
● Experience developing APIs using FastAPI or Flask.
● Working knowledge of SQL/MySQL, Redis, and cloud deployment (AWS/Azure).
● Familiarity with Docker, Git, and production deployment practices.