AI / Machine Learning Engineer

🌟 About the Role & Team: Zomato AI Labs is pioneering artificial intelligence for hyper-local commerce, autonomous menu digitization, visual food recognition, and multi-lingual conversational ordering agents. You will work on cutting-edge generative AI models and large-scale recommendation systems processing billions of events daily. 🎯 Key Responsibilities: • Train, fine-tune, and evaluate deep learning, NLP, and computer vision models using PyTorch and HuggingFace Transformers. • Build Retrieval-Augmented Generation (RAG) pipelines and LLM agents using LangChain, LlamaIndex, and Vector DBs (Milvus / Pinecone). • Deploy optimized inference engines using ONNX Runtime, TensorRT, and FastAPI on GPU-accelerated Kubernetes clusters. • Run rigorous A/B experiments and feature engineering to maximize recommendation click-through rates (CTR) and conversion. • Research and implement state-of-the-art papers in generative AI, multi-modal embeddings, and reinforcement learning. 💼 Qualifications & Technical Requirements: • B.Tech / M.Tech / MS in Computer Science, Artificial Intelligence, Data Science, or Mathematics. • Strong mathematical foundation in Linear Algebra, Probability, Calculus, and Deep Learning algorithms. • Proficiency in Python, NumPy, Pandas, Scikit-learn, and at least one deep learning framework (PyTorch / TensorFlow). • Experience building and exposing machine learning models via RESTful APIs (FastAPI / Flask). 🚀 Preferred & Bonus Skills: • Published research in top-tier conferences (NeurIPS, ICML, CVPR, ACL) or top ranks in Kaggle competitions. • Experience with Large Language Model fine-tuning (LoRA, QLoRA) and prompt engineering. • Familiarity with MLOps pipelines (MLflow, Kubeflow, Weights & Biases). 🎁 Compensation, Benefits & Career Growth: • CTC: ₹15,00,000 per annum + Generous Equity (ESOPs) + Annual Research Grant. • Dedicated cloud compute credits on NVIDIA H100 GPU clusters for personal research. • Health & Life Insurance + Relocation Allowance to Delhi NCR. • Direct collaboration with PhD AI Researchers and Stanford/IIT Alumni. ⚡ Hiring & Evaluation Process: 1. Technical Resume & AI Project Portfolio Review 2. Algorithmic Coding + Machine Learning Mathematical Assessment (75 mins) 3. Model Architecture & RAG Pipeline Design Round 4. Founder / Head of AI Discussion & Offer Release