Senior Artificial Intelligence Engineer

Responsibilities

• Design, develop, and optimize recommendation systems, including collaborative filtering, content-based methods, and deep learning-based approaches.
• Build and apply algorithms for user behavior analysis, segmentation, and personalization.
• Develop RAG-based information retrieval systems.
• Fine-tune and deploy commercial & open-source LLMs.
• Design data acquisition and labeling processes, and develop data quality control algorithms.
• Lead AI projects, mentor junior team members, and collaborate effectively with interdisciplinary teams.
• Stay updated on state-of-the-art technologies and deliver proofs-of-concept (PoCs) to evaluate their relevance to product requirements.
• Understand business objectives and develop models to achieve them, along with metrics to track progress.
• Participate in design and code reviews, facilitate discussions, and align on architectural and strategic decisions.

Qualifications

• BSc degree in Computer Engineering, Industrial Engineering, Mathematical Engineering, Artificial Intelligence, or related fields.
• At least 4 years of experience in data science and MLOps.
• Strong proficiency in Python programming and data science libraries.
• Familiarity with recommendation systems algorithms and concepts.
• Experience in modeling for NLP tasks.
• Hands-on experience with frameworks for building and integrating LLM-based applications.
• Solid understanding of Retrieval-Augmented Generation (RAG).
• Experience with SQL/NoSQL and database structures.
• Familiarity with CI/CD processes.
• Experience with Docker and Kubernetes technologies.
• Experience with PyTorch, TensorFlow, XGBoost, CatBoost, LightGBM, Hugging Face, and OpenAI tools.
• Proficiency in written and spoken English.
• Ability and motivation to self-teach, enter new domains, and manage ambiguity.



Preferred / Nice-to-have Qualifications

• A MSc degree or Ph.D. in a relevant field.
• Solid academic or industrial experience in recommendation systems, user profiling, and human-computer interaction.
• Experience with Kubeflow technology.
• Familiarity with modern big data solutions and distributed computing platforms.
• Hands-on experience with vector and graph database technologies.
• Experience with cloud-based AI services.
• Hands-on experience with LangChain, LLamaIndex, or similar frameworks and libraries.
• Understanding of explainable AI concepts and applications.
• Experience in one of the following areas—knowledge bases, network analysis, Graph Neural Networks (GNNs), or Reinforcement Learning (RL)—is desirable.