AI/ML Engineer

🚀 About the Role

We are seeking a highly skilled and innovative AI/ML Engineer with 4–6 years of hands-on

experience in Machine Learning, Generative AI, and Large Language Models (LLMs). The

ideal candidate should have deep expertise in modern AI frameworks, vector databases,

open-source LLMs, and prompt engineering. You will play a pivotal role in designing, building,

and deploying LLM-powered applications, including RAG pipelines, Agentic AI, and MCP

workflows.

🧩 Key Responsibilities

● Design, develop, and deploy AI/ML models for real-world applications.

● Implement Generative AI solutions using platforms like OpenAI, Anthropic Claude, and

HuggingFace Transformers.

● Work on LLM fine-tuning using PEFT, LoRA, QLoRA, and similar parameter-efficient

methods.

● Develop intelligent agents using LangChain and LangGraph frameworks.

● Build and optimize RAG pipelines integrated with vector databases like Pinecone,

Weaviate, etc.

● Apply prompt engineering techniques to improve model performance and outputs.

● Collaborate cross-functionally with product, data, and engineering teams to deliver

scalable AI systems.

● Work with cloud infrastructure, especially AWS, for model training, deployment, and

orchestration.

● Stay up to date with the latest research and trends in AI, LLMs, and agent-based

systems.

● Implement and maintain MCP Protocols and agentic workflows for advanced

decision-making pipelines.

Must-Have Skills & Experience

● 4–6 years of strong experience in Machine Learning, Deep Learning or Generative AI

and Agentic AI

● Hands-on experience with Generative AI, LLM architectures, and open-source

models like Mistral, Meta LLaMA, etc.

● Proficiency in LangChain, LangGraph, and prompt engineering

● Familiarity with Vector Databases such as Pinecone, Weaviate, FAISS, etc.

● Experience with OpenAI, HuggingFace, Anthropic Claude, and model APIs

● In-depth understanding of LLM fine-tuning techniques (LoRA, QLoRA, PEFT)

● Strong Python programming skills and experience with ML frameworks (PyTorch,

TensorFlow)

● Good understanding of AWS services for model training, hosting, and storage

● Solid understanding of RAG pipelines, agentic AI frameworks, and MCP Protocols

● Experience working in a fast-paced, research-driven environment