7.0 - 12.0 years

20 - 35 Lacs

Hyderabad

Remote

Roles & responsibilities Serve as the AI & data strategist , discovering and onboarding new data sources and shaping end-to-end pipelines that span traditional analytics, machine learning (ML), deep learning (DL), natural-language processing (NLP), generative AI (Gen AI), and agentic AI . Partner with engineering to design, build, and harden production-grade data and AI products (e.g., RAG search, LLM-powered assistants, anomaly-detection services). Run analytical experiments classification, forecasting, LLM fine-tuning, prompt-engineering A/B tests to solve business problems across multiple domains. Collect, clean, and enrich large structured, semi-structured, and unstructured datasets (text, image, audio, sensor, graph). Design, train, and validate classical ML models, DL architectures (CNN, RNN, Transformers), and instruction-tuned LLMs ; measure drift and conduct error analysis to drive iterative improvement. Implement retrieval-augmented generation and agentic task-planning pipelines that combine vector search, function calling, and tool invocation. Document findings, publish reusable components, and mentor junior data scientists and ML engineers. Qualifications Experience Proven experience in delivering data-driven solutions, with demonstrable depth in at least two of: ML, DL, NLP, GenAI, agentic AI. Hands-on proficiency in Python (pandas, NumPy, scikit-learn), DL frameworks (TensorFlow or PyTorch), and LLM / GenAI toolkits (Hugging Face Transformers, LangChain/LangGraph, Google ADK). Proven track record in feature engineering, pattern recognition, predictive modeling, and LLM fine-tuning / evaluation . Experience optimizing GPU / TPU workloads and scaling distributed training or inference. Familiarity with vector databases (FAISS, Chroma, Pinecone) and distributed data systems (Spark, BigQuery, Snowflake). sibilities Preferred candidate profile

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