#астана #python #ai
AI EngineerTil-Qazyna National Scientific and Practical Center
Astana | Office:
Alem.ai | Mon–Fri, 08:00–17:30
700,000 KZT gross
About Us & The TeamTil-Qazyna is a national scientific and practical center dedicated to building the core digital and AI infrastructure for the Kazakh language. We develop foundational language resources, linguistic tools, and open-source models, including custom text corpora, morphological analyzers, RAG pipelines, and fine-tuned Large Language Models.
We are looking for an
AI Engineer to focus exclusively on natural language processing, corpus engineering, and LLM fine-tuning.
Key Responsibilities•
LLM Adaptation & Fine-Tuning: Fine-tune, evaluate, and benchmark open-source LLMs (Llama, Mistral, Qwen, Gemma) for Kazakh language understanding and generation using parameter-efficient methods (LoRA, QLoRA, PEFT).
•
NLP & Linguistic Tooling: Develop, maintain, and optimize rule-based and neural NLP components, including morphological analyzers, lemmatizers, tokenizers, and terminology parsers.
•
Corpus & Data Pipelines: Design automated pipelines for large-scale text crawling, data cleaning, deduplication, synthetic data generation, and dataset curation.
•
Inference & Deployment: Package NLP models and LLMs into containerized microservices (Docker, FastAPI) and optimize inference using modern serving frameworks (vLLM, Ollama, TensorRT-LLM, ONNX).
Requirements• 1+ years of hands-on experience as NLP / AI / Machine Learning engineer.
• Solid understanding of the Transformer architecture, attention mechanisms, embeddings, and tokenization.
• Experience with core ML/NLP libraries:
PyTorch, Hugging Face (transformers, datasets, accelerate, peft),
Scikit-learn.
• Experience building data preprocessing pipelines and working with structured/unstructured text data.
• Practical knowledge of
Docker, Linux, and
Git.• Degree in Computer Science, Data Science, Applied Mathematics.
Nice to Have• Hands-on experience with modern LLM serving and optimization engines (vLLM, TGI, llama.cpp, quantization techniques like AWQ/GPTQ).
• Experience with RAG stacks (LangChain, LlamaIndex, ChromaDB, Qdrant, FAISS).
• Understanding of the morphological, agglutinative, or grammatical characteristics of the Kazakh language.
• Familiarity with alignment techniques (DPO, RLHF) or synthetic data generation.
What We Offer• Direct impact on sovereign AI development and language technology used at scale.
• Official employment in full compliance with the Labor Code of the Republic of Kazakhstan.
• Access to high-performance GPU compute clusters for model training and experimentation.
To ApplySend your CV to
@b4wer on Telegram.
info@tilqazyna.kz