Must have

• AI

• Python

• Data analysis

• SQL

• English

Nice to have

• CI/CD Pipelines

• AI agents

• LangChain

Requirements description

Requirements:

• 5+ years of experience in commercial software engineering with a focus on machine learning or AI.
• Expertise in transformer models and natural language processing.
• Strong proficiency in 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 skills in English, both written and verbal.”

Nice to have:

• Experience with CI/CD pipelines

• Experience with RAG systems and retrieval augmented generation pipelines.

• Experience with AI agent frameworks (LangChain/LlamaIndex/Haystack).

Offer description

Target:

As an AI Software Engineer you will design, develop, and maintain high‑performance inference services and training pipelines for text‑classification models. You will collaborate with product owners, and R&D teams to turn research prototypes into production‑grade solutions, while continuously improving model quality and operational reliability. The main development language is Python and ML library is Torch with Hugging Face Transformers.

What we offer:

• Full time office work in Wola, Warsaw

• Contract of employment, Agency agreement

• Private healthcare package. We offer premium private healthcare package for our employees.

• Sport Cards. Our employees can choose from many options within sport subscriptions and sport associations.

• Benefit Platform. You can choose your benefits on our Benefit Platform e.g.: cinema/theater tickets and discounts, shopping cards and many more.

• Special discounts for employees. We cooperate with various local companies to offer unique promotions only for our Employees.

• Office massages. It is a 15-minute chair-based

Your responsibilities

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