AI Engineer / Researcher

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.

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.

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.

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.