Posted:11 hours ago|
Platform:
On-site
Full Time
🚀 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
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