Data Scientist

Role: Data Scientist Location: Gachibowli, Hyderabad Work Mode: Hybrid Experience : 2-4 years Notice period: Immediate to 30 days Note : Face to Face Discussion is mandatory for this role Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for our customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence. Role Summary We are seeking a skilled Data Scientist with expertise in Generative AI and LLMOps to design, develop, and deploy scalable AI solutions. This role focuses on building production-grade LLM applications, including RAG pipelines, prompt engineering, and model optimization. Key Responsibilities Design and develop Generative AI solutions using Large Language Models (LLMs) Build and optimize Retrieval-Augmented Generation (RAG) pipelines Deploy and manage LLM-based applications in production environments Perform prompt engineering, tuning, and evaluation Integrate LLMs with APIs, databases, and enterprise systems Work with vector databases and embedding models Monitor model performance, reduce hallucinations, and improve response quality Optimize systems for latency, scalability, and cost efficiency Collaborate with cross-functional teams to solve business problems using AI Required Skills & Qualifications Generative AI / LLM Hands-on experience with LLMs (OpenAI, open-source models, etc.) Strong understanding of prompt engineering techniques Experience building RAG-based applications Knowledge of fine-tuning / model adaptation (LoRA, PEFT preferred) LLMOps Experience in deploying and managing LLM applications in production Understanding of model lifecycle, monitoring, and logging Experience with performance optimization and evaluation Machine Learning Foundation Strong understanding of ML algorithms and concepts Experience with model evaluation techniques and metrics Data preprocessing and feature engineering experience Tools & Technologies Strong proficiency in Python (Pandas, NumPy, Scikit-learn) Experience with frameworks like LangChain, LlamaIndex (or similar) Hands-on with vector databases (Pinecone, FAISS, Weaviate, etc.) Cloud platforms: AWS / Azure / GCP Experience with APIs, Docker, and microservices Preferred Qualifications Experience building end-to-end GenAI applications Exposure to AI agents / multi-step workflows Domain experience in insurance, fintech, or healthcare Familiarity with MLOps practices