Data Architect Lead

2 days ago

agra, India beBeeData Full time

AI Innovation LeadJob Summary:We are seeking a Senior Data Scientist to spearhead the development of cutting-edge generative AI, LLM, and agentic systems. As an AI Innovation Lead, you will drive business growth through high-impact AI solutions, leading projects end-to-end from research and prototyping to production deployment.Responsibilities:Design, develop, and deploy advanced generative AI models (LLMs, diffusion, multi-agent systems)Own AI projects end-to-end: ideation, proof-of-concept, scalable deployment, and monitoringDevelop high-performance ML/DL models using state-of-the-art architecturesWork on RAG pipelines, agent orchestration, fine-tuning, computer vision, and optimizationCollaborate with cross-functional teams to deliver production-grade AI systemsTechnical Skills:You will require expertise in:Python (advanced), multiprocessing/async programmingPyTorch, TensorFlow, JAXHuggingFace Transformers/DiffusersLangChain, LangGraph, LlamaIndex, Semantic KernelMLOps: MLflow, W&B, KubeflowCUDA, CuPy, CuGraphGenerative & Agentic AI:Experience with RAG (standard, graph-based, vector DBs like FAISS, Pinecone, Weaviate, Milvus)Multi-agent orchestration (LangGraph, AutoGen, Semantic Kernel)Fine-tuning diffusion models (Stable Diffusion, Flux.1, ControlNet, DreamBooth)LLM fine-tuning (LoRA, QLoRA) on Llama3, Mistral, CodeLlama, Falcon, GemmaAdvanced prompt engineering & function callingML & Deep Learning:XGBoost, LightGBM, CatBoost, clustering, PCA/UMAPCNNs, RNNs/LSTMs, Transformers (BERT, ViT, GPT)GNNs (GraphSAGE, GAT), Time-series (Prophet, TFT)RL: PPO, DQN, RLHFComputer Vision:YOLO (v5–v8), DETR, Faster R-CNNOCR: PaddleOCR, Tesseract, EasyOCR, LayoutLMVideo analytics: DeepSORT, ByteTrackMulti-modal: CLIP, BLIP, SAM, Florence-2Optimization & Deployment:TensorRT, ONNX, quantization, pruning, distillationDocker, Kubernetes, REST/gRPC APIsAzure ML, Azure OpenAI, App ServicesMonitoring: Prometheus, Grafana, Azure Monitor, ELKQualifications:Bachelor's or Master's in Computer Science or related field3.5–7 years experience in ML/AI with proven end-to-end solution deliveryStrong fundamentals in ML/DL, optimization, modelingExperience deploying production-level ML/LLM solutionsPublications, open-source contributions, or patents are a plusExcellent analytical, debugging & problem-solving skills

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