Lead Data Scientist

08-01-2026

156

Develop and fine-tune transformer-based models specifically for the Azerbaijani language.
Work with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems to enhance AI-driven capabilities.
Contribute to the development of AI applications, improving the accuracy and efficiency of language models and related technologies.
Develop and optimize Retrieval-Augmented Generation (RAG) systems for improving information retrieval and response generation.
Design and optimize algorithms for entity recognition, text summarization, and semantic search.

2+ years of professional experience in Data Science with a strong focus on NLP and LLM applications.
Hands-on experience building and deploying LLM-powered chatbots, mainly in on-premise environments.
Strong knowledge of RAG systems: document chunking, embeddings, retrieval strategies, and vector databases (FAISS, Pinecone, Weaviate).
Practical experience with Azerbaijani NLP tasks: classification, NER, sentiment analysis, text generation, and translation.
Solid understanding of transformers and foundation models (BERT, GPT, T5, LLaMA, etc.).
Experience with LLM evaluation, testing, and prompt optimization.
Proficient in PyTorch, TensorFlow, Hugging Face ecosystem, and embedding-based similarity search.
Expertise in LLM optimization (LoRA, quantization, distillation) for efficient on-prem deployment.
Experience with LLM serving frameworks (vLLM, Ollama, TGI) and RAG/agent frameworks (LangChain, LlamaIndex).
Skilled in CI/CD for ML, model tracking (MLflow/W&B), Docker, Kubernetes, and monitoring.
Familiar with secure and compliance-heavy environments (public sector, healthcare, finance).