AI Engineer / Researcher

Tasks

• Analyze business problems and select suitable ML/LLM approaches for specific use cases.

• Build proofs of concept, run model benchmarks, and evaluate quality, cost, and scalability.

• Design and maintain data pipelines for preparation, cleaning, anonymization, and feature engineering.

• Build dataset repositories and data versioning processes for experiments and production workloads.

• Develop the internal AI platform: inference APIs, prediction monitoring, and automated training/deployment.

• Integrate language models with company systems, including RAG layers and prompt management.

• Support product teams with architecture guidance, reusable AI components, documentation, and training.

Requirements

• At least 3 years of experience in AI/ML or Data Science Engineering.

• Hands-on experience with Python and the ML/LLM ecosystem (e.g., OpenAI, Hugging Face).

• Experience building data pipelines and working with production-scale datasets.

• Understanding of MLOps practices and model deployment automation.

• Ability to design APIs and integrate AI services with business systems.

• Knowledge of data security, access control, and AI governance.

• Strong analytical thinking and technical communication skills.

• Good command of English for technical documentation and collaboration.

Nice to Have

• Experience with cloud platforms and GPU workloads.

• Knowledge of RAG solutions, vector databases, and LLM response quality evaluation.

• Experience in regulated or mission-critical environments.

• Familiarity with model drift monitoring and AI ethics risk management.

We Offer

• A key role in building an internal AI platform with real organizational impact.

• Work with a modern tool stack and high technical autonomy.

• Growth opportunities in GenAI, MLOps, and data platform architecture.

• Stable employment terms and a collaborative work environment.

We offer

• Work in a friendly, well-coordinated team of enthusiasts

• Stable employment in a modern company with an established market position

• Attractive salary and benefits package (e.g., private medical care, sports card)

• Opportunities for professional development and participation in innovative projects