New job·
AI Engineer at Til-Qazyna National Scientific and Practical Center
ML Jobs
600,000 to 700,000 KZT Gross per month · Astana / Office
Til-Qazyna builds digital and AI infrastructure for the Kazakh language, including foundational language resources and open-source models. The team develops linguistic tools, custom text corpora, morphological analyzers, and fine-tuned large language models.
Til-Qazyna builds digital and AI infrastructure for the Kazakh language, including foundational language resources and open-source models. The team develops linguistic tools, custom text corpora, morphological analyzers, and fine-tuned large language models.
600,000 to 700,000 KZT Gross per month · Astana / Office
Responsibilities4
• Fine-tune, evaluate, and benchmark open-source LLMs for Kazakh using LoRA, QLoRA, and PEFT.
• Develop and optimize rule-based and neural NLP components, including morphological analyzers, lemmatizers, tokenizers, and terminology parsers.
• Build pipelines for text crawling, cleaning, deduplication, synthetic data generation, and dataset curation.
• Package NLP models into Docker and FastAPI microservices and optimize inference with vLLM, Ollama, TensorRT-LLM, or ONNX.
• Develop and optimize rule-based and neural NLP components, including morphological analyzers, lemmatizers, tokenizers, and terminology parsers.
• Build pipelines for text crawling, cleaning, deduplication, synthetic data generation, and dataset curation.
• Package NLP models into Docker and FastAPI microservices and optimize inference with vLLM, Ollama, TensorRT-LLM, or ONNX.
Requirements5
• 1+ years of hands-on NLP, AI, or machine learning engineering experience.
• Understanding of Transformers, attention mechanisms, embeddings, and tokenization; experience with PyTorch, Hugging Face libraries, and Scikit-learn.
• Experience building preprocessing pipelines for structured and unstructured text data.
• Practical knowledge of Docker, Linux, and Git.
• Degree in Computer Science, Data Science, or Applied Mathematics.
• Understanding of Transformers, attention mechanisms, embeddings, and tokenization; experience with PyTorch, Hugging Face libraries, and Scikit-learn.
• Experience building preprocessing pipelines for structured and unstructured text data.
• Practical knowledge of Docker, Linux, and Git.
• Degree in Computer Science, Data Science, or Applied Mathematics.
Optional3
• Experience with LLM serving and optimization, including vLLM, TGI, llama.cpp, AWQ, or GPTQ.
• Experience with RAG stacks such as LangChain, LlamaIndex, ChromaDB, Qdrant, or FAISS.
• Understanding of Kazakh morphological, agglutinative, or grammatical characteristics; familiarity with DPO, RLHF, or synthetic data generation.
• Experience with RAG stacks such as LangChain, LlamaIndex, ChromaDB, Qdrant, or FAISS.
• Understanding of Kazakh morphological, agglutinative, or grammatical characteristics; familiarity with DPO, RLHF, or synthetic data generation.