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.)
Solid 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

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