About the Role :

We are looking for a passionate Machine Learning Engineer with hands-on experience in Large Language Models (LLMs), Generative AI, NLP, and Conversational AI. The ideal candidate should have strong expertise in designing, developing, and deploying AI-powered applications that leverage up-to-date deep learning frameworks and cloud technologies. You will be responsible for building scalable AI solutions, developing intelligent automation systems, creating conversational AI applications, and integrating foundation models into enterprise products.

Key Responsibilities :

- Design, build, and deploy Machine Learning and Generative AI applications.
- Develop AI-powered products using Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, or similar models.
- Build conversational AI solutions including chatbots, virtual assistants, and intelligent automation workflows.
- Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
- Fine-tune, optimize, and evaluate transformer-based models for various NLP tasks.
- Implement recommendation systems and intelligent search solutions.
- Develop scalable REST APIs and AI microservices using Python frameworks such as Django or Flask.




- Integrate AI solutions with cloud platforms including AWS or GCP.
- Work closely with Product, Engineering, and Data teams to translate business problems into AI solutions.
- Optimize model inference, latency, scalability, and production deployment.
- Conduct experimentation, model evaluation, and continuous improvement of AI systems.
- Stay updated with the latest advancements in Generative AI, LLMs, and Machine Learning.

Qualifications :

- 2 to 4 years of hands-on experience in Machine Learning, Deep Learning, or Artificial Intelligence.
- Strong proficiency in Python programming.
- Hands-on experience with Large Language Models (LLMs) and Generative AI applications.
- Strong understanding of Natural Language Processing (NLP), Conversational AI, and Recommendation Systems.
- Experience working with deep learning frameworks such as PyTorch and/or TensorFlow.
- Experience with Hugging Face Transformers, prompt engineering, and LLM integration.
- Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector databases (FAISS, Pinecone, ChromaDB, or similar) is preferred.

📌 Machine Learning Engineer - LLM/RAG (India)
🏢 Think Future Technologies
📍 India