Data Architect

4 days ago


alwar, India beBeeData Full time

Lead Data InnovatorHiring a seasoned Lead Data Innovator to spearhead cutting-edge Generative AI, LLM, and agentic system development. This role involves transforming complex business challenges into impactful AI solutions by leading projects end-to-end from research and prototyping to production deployment.About the RoleResearch, design & build advanced generative AI models (LLMs, diffusion, multi-agent systems) with a strong focus on innovation and collaboration.Own AI projects from ideation to proof-of-concept, scalable deployment, and monitoring to ensure seamless delivery.Develop high-performance ML/DL models using state-of-the-art architectures to drive business growth.Work on RAG pipelines, agent orchestration, fine-tuning, computer vision, and optimization to maximize efficiency.Technical SkillsProgramming: Advanced Python skills, experience with multiprocessing/async programming, and proficiency in PyTorch, TensorFlow, JAX.Familiarity with HuggingFace Transformers/Diffusers, LangChain, LangGraph, LlamaIndex, Semantic Kernel, MLOps tools like MLflow, W&B, Kubeflow, CUDA, CuPy, CuGraph.Generative & Agentic AIRAG (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).Advanced prompt engineering & function calling, LLM fine-tuning (LoRA, QLoRA) on Llama3, Mistral, CodeLlama, Falcon, Gemma.Mixed Methods & Deep LearningXGBoost, LightGBM, CatBoost, clustering, PCA/UMAP for data analysis and visualization.CNNs, RNNs/LSTMs, Transformers (BERT, ViT, GPT), GNNs (GraphSAGE, GAT), Time-series (Prophet, TFT) for predictive modeling.RL: PPO, DQN, RLHF for decision-making and policy optimization.Computer VisionYOLO (v5–v8), DETR, Faster R-CNN for object detection and recognition.OCR: PaddleOCR, Tesseract, EasyOCR, LayoutLM for text extraction and processing.Video analytics: DeepSORT, ByteTrack for tracking and monitoring.Multi-modal: CLIP, BLIP, SAM, Florence-2 for image-text fusion.Optimization & DeploymentTensorRT, ONNX, quantization, pruning, distillation for model optimization.Docker, Kubernetes, REST/gRPC APIs for containerization and orchestration.Azure ML, Azure OpenAI, App Services for cloud-based AI solutions.Monitoring: Prometheus, Grafana, Azure Monitor, ELK for performance tracking.RequirementsBachelor's or Master's degree in Computer Science or related field.3.5–7 years of experience in ML/AI with proven end-to-end solution delivery.Strong fundamentals in ML/DL, optimization, modeling, excellent analytical, debugging & problem-solving skills.Prior experience deploying production-level ML/LLM solutions, publications, open-source contributions, or patents are a plus.



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