Süni İntellekt üzrə Aparıcı Mühəndis (LLM / NLP)

About the role

We are looking for a Lead AI Engineer to design and implement cutting‑edge artificial intelligence and machine‑learning solutions that meet our business needs. You will work on large language model (LLM) based applications, natural language processing (NLP) pipelines, and integrate them into existing platforms.

Key responsibilities

• Develop AI and ML solutions aligned with business requirements.
• Process and analyze text and other unstructured data.
• Build LLM‑based solutions and integrate them with current systems.
• Prepare, clean, and adapt datasets for modeling.
• Test models, evaluate results, and optimise performance.
• Integrate AI models via REST APIs and micro‑services.
• Monitor and improve solution accuracy, reliability and performance.
• Produce technical documentation and follow code‑quality standards.
• Research and apply emerging AI technologies and approaches.

Required profile

• Higher education in Computer Engineering, Computer Science, Applied Mathematics or a related field.
• At least 2 years of professional experience in AI, machine learning, data science or a related area.
• Strong proficiency in Python.
• Practical experience with NLP and text processing.
• Experience fine‑tuning LLMs, using LoRA and quantisation techniques.
• Ability to work with vector databases.
• Familiarity with open‑source LLM and NLP models.
• Knowledge of text and speech data processing.
• Hands‑on experience with PyTorch, TensorFlow or a similar ML framework.
• Competence with Hugging Face Transformers, spaCy or comparable libraries.
• Understanding of Prompt Engineering, embeddings and Retrieval‑Augmented Generation (RAG).
• Experience building REST APIs and micro‑service architectures.
• SQL and database handling skills.
• Knowledge of model evaluation methods and metrics.
• Good command of English or Russian.

Required skills

• Python
• NLP
• LLM fine‑tuning
• LoRA
• Quantisation
• Vector databases
• Open‑source LLM models
• Text and speech processing
• PyTorch
• TensorFlow
• Hugging Face Transformers
• spaCy
• Prompt Engineering
• Embeddings
• Retrieval‑Augmented Generation (RAG)
• REST API
• Micro‑services
• SQL
• Model evaluation metrics