Role & responsibilities
Build, train, evaluate, and deploy predictive machine learning models.
Design and develop LLM-powered applications and intelligent AI agents.
Build and implement Retrieval-Augmented Generation (RAG) pipelines.
Fine-tune Large Language Models using techniques.
Perform feature engineering, data preprocessing, model training, and performance evaluation.
Work with vector databases for efficient document retrieval and semantic search.
Design and develop multi-step agent workflows for complex problem-solving.
Integrate AI solutions with APIs, applications, and business workflows.
Optimize AI/ML models and applications for scalability, accuracy, and performance.
Collaborate with cross-functional teams including software developers, data engineers, product teams, and business stakeholders.
Stay updated with emerging technologies and best practices in Machine Learning, Generative AI, LLMs, and agent-based systems.

Mandatory Technical Skills

Programming & Machine Learning
Expert-level proficiency in Python.
Strong working knowledge of SQL.




Hands-on experience with Scikit-learn, XGBoost, and LightGBM.
Experience with Pandas and NumPy.
Solid understanding of feature engineering, data preprocessing, and model evaluation.
Good knowledge of evaluation metrics such as F1 Score, AUC-ROC, Precision, Recall, and Precision-Recall.

Deep Learning & LLMs
Hands-on experience with PyTorch or TensorFlow.
Robust experience with Hugging Face Transformers.
Experience building applications using OpenAI and Anthropic APIs.
Hands-on experience with LangChain and/or LlamaIndex.
Practical experience in LLM fine-tuning, including LoRA, QLoRA, and PEFT.

RAG & Vector Databases
Solid hands-on experience building RAG pipelines.
Experience working with vector databases such as:
Pinecone
Milvus
Weaviate
Understanding of document retrieval, embeddings, chunking, and semantic search.

AI Agents
Experience developing auton

📌 Ai Ml Engineer Mumbai Suburban
🏢 B2W Infotech
📍 Mumbai Suburban