We are a product-driven IT company with over 10 years of experience in the digital advertising market.
We develop and continuously improve a high-load advertising platform that processes over 10 billion events daily and stores data in a 3.6-petabyte ClickHouse cluster.
Our infrastructure includes 500+ servers located across data centers in Europe and the USA, handling over 1 million requests per second during peak hours.
We combine deep technological expertise and advanced analytics to ensure the stability, scalability, and efficiency of our global advertising ecosystem.
About the Role:
We are expanding our Applied AI division and are looking for an AI Engineer who can design and implement solutions based on Large Language Models (LLMs).
The role covers the full development cycle — from building pipelines and fine-tuning models to integrating them into real products and internal company processes.
The engineer will collaborate closely with the Data Science and Platform teams, working with large datasets and applying modern NLP, RAG, and prompt engineering methods to enhance and optimize business tools.
This role involves the practical application of LLMs in automation, content analysis and generation, as well as developing internal AI tools and training employees to use them effectively.
What You’ll Be Doing:
- Designing and integrating LLM-based solutions into internal and client-facing products;
- Building and refining chatbots, assistants, and recommendation systems;
- Developing fine-tuning and RAG pipelines for model improvement;
- Processing large volumes of textual and multimodal data — cleaning, preparing, and structuring it; Applying prompt engineering techniques to optimize generation quality;
- Embedding LLMs into business workflows — information retrieval, support automation, code review assistance, and documentation generation;
- Evaluating model performance — quality metrics, A/B testing, and user feedback loops;
- Collaborating with Data Scientists and the Platform Team; Writing MCPs (Model Control Policies);
- Conducting LLM training sessions for employees on both general and internal tools (e.g., via MCP).
What Will Help You Succeed:
- Experience with workflow automation tools (e.g., n8n);
- Strong knowledge of Python and modern ML/AI frameworks (PyTorch, TensorFlow, JAX);
- Solid understanding of NLP and LLM architectures;
- Hands-on experience with RAG frameworks;
- Proficiency in version control systems (Git);
- Understanding of MLOps principles;
Awareness of information security and safe LLM usage practices.
Nice to Have:
- Experience with SQL and data storage systems (PostgreSQL, ClickHouse, Spark, Flink);
- Basic knowledge of Kubernetes (k8s).
What We Offer:
- No dress code and minimal bureaucracy;
- Choice between a MacBook or Windows laptop;
- Health insurance and mobile plan coverage;
- Free lunches and drinks;
- Fresh fruits and snacks in the office every day;
- Free English classes; Fitness reimbursement;
- Partial coverage (50% gross) for kindergartens and schools.
