Cutting-Edge AI Solutions Specialist

6 days ago

dindigul, India beBeeDataScientist Full time

Lead AI InnovatorTransform business challenges into impactful AI solutions by building and deploying cutting-edge Generative AI, LLM, and agentic systems.We are seeking an exceptional Senior Data Scientist who can lead end-to-end projects from ideation to scalable production deployment.Key Responsibilities:Research and design advanced generative AI models including LLMs, diffusion, and multi-agent systems.Own AI projects: ideation, proof-of-concept, scalable deployment, and monitoring.Develop high-performance ML/DL models using state-of-the-art architectures.Collaborate with cross-functional teams to deliver production-grade AI systems.Required Skills:Advanced Python programming skills and multiprocessing/async development experience.Proficiency in PyTorch, TensorFlow, JAX, HuggingFace Transformers, and Diffusers.Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, MLOps (MLflow, W&B, Kubeflow), CUDA, CuPy, and CuGraph.Generative & Agentic AI:Expertise in RAG (standard, graph-based), vector DBs like FAISS, Pinecone, Weaviate, and Milvus.Multi-agent orchestration skills using LangGraph, AutoGen, and Semantic Kernel.Fine-tuning diffusion models including Stable Diffusion, Flux.1, ControlNet, and DreamBooth.LLM fine-tuning on Llama3, Mistral, CodeLlama, Falcon, and Gemma.ML & Deep Learning:Experience with XGBoost, LightGBM, CatBoost, clustering, PCA/UMAP, CNNs, RNNs/LSTMs, and Transformers.Skills in GNNs (GraphSAGE, GAT), Time-series (Prophet, TFT), and RL: PPO, DQN, and RLHF.Computer Vision:Knowledge of YOLO (v5–v8), DETR, Faster R-CNN, OCR: PaddleOCR, Tesseract, EasyOCR, and LayoutLM.Experience with video analytics: DeepSORT, ByteTrack, and multi-modal: CLIP, BLIP, SAM, and Florence-2.Optimization & Deployment:Skills in TensorRT, ONNX, quantization, pruning, distillation, Docker, Kubernetes, REST/gRPC APIs.Experience with Azure ML, Azure OpenAI, App Services, monitoring tools: Prometheus, Grafana, and ELK.Qualifications:Bachelor's or Master's degree in Computer Science or related field.3.5–8 years experience in ML/AI with proven end-to-end solution delivery.Strong fundamentals in ML/DL, optimization, modeling.Experience deploying production-level ML/LLM solutions.

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