AI Software Engineer ML/NLP

• Private healthcare package. We offer premium private healthcare package for employees.
• Sport Cards. Employees can choose from many options within sport subscriptions and sport associations.
• Benefit Platform. Employees can choose the benefits on Benefit Platform e.g.: cinema/theater tickets and discounts, shopping cards and many more.
• Special discounts for employees. Our cooperates with various local companies to offer unique promotions only for our Employees.
• Office massages. It is a 15-minute chair-based massage. The massage therapist focuses on your back, neck, shoulders and arms.
• Annual bonus
• Work in internation enviroment at R&D center
• Work with very experienced team at large scale projets
• Long-term cooperation with contact of employment

• 5+ years of experiencein commercial software engineering with a focus on machine‑learning or AI.
• Expertise in transformer modelsand natural language processing.
• Strong proficiencyin Python and deep‑learning frameworks (PyTorch, TensorFlow).
• Strong analytical mindset: exploratory data analysis, feature engineering, model evaluation.
• Solid data‑engineering skills: SQL (PostgreSQL) and NoSQL (Redis, MongoDB) data handling, ETL, and data‑preparation for training.
• Excellent communication skillsin English, both written and verbal.

Nice to have:

• Experience with CI/CD pipelines
• Experience with RAG systemsand retrieval‑augmented generation pipelines.
• Experience with AI agent frameworks(LangChain/LlamaIndex/Haystack).

Responsibilities

• Develop, train, and fine‑tune machine‑learning models for a variety of natural‑language processing tasks, ensuring optimal performance and reproducibility.
• Build and maintain inference servers for text‑classification workloads based on BERT and other transformer architectures.
• Provide AI consulting to R&D projects, translating technical insights into actionable product decisions.
• Maintain and improve automated retraining pipelines that ingest new data, evaluate model drift, and trigger scheduled or on‑demand model updates.
• Create PoCs and MVPs for emerging AI use‑cases, translating business requirements into technical specifications and deliverable prototypes/MVPs.