You + Miquido = Classic Machine Learning solutions: Designing and developing robust ML models for real-world problems. Focus areas include predictive analytics, recommendation systems, credit scoring, churn prediction, and computer vision. Data mastery: You are the architect of the data. You will handle complex data cleaning, manipulation, and preparation to ensure high-quality inputs for model training. Solution architecture: Selecting the 'best tool for the job'—whether that is a simple regression model or a complex neural network—based on client constraints and business value. Tech consulting: You will play a key role in the pre-sales process. This includes meeting with clients to understand their business needs, actively participating in workshops to discover AI potential, estimating workload/costs, and translating abstract requirements into concrete, actionable technical plans. Project delivery: Taking ownership of the AI component in projects from conceptualisation to delivery, ensuring they align with the client's strategy and Miquido’s standards. Strategy: Working with stakeholders to identify opportunities for AI-driven innovation. You can be the perfect match for us if you have:The Core (Must Haves): Strong Proficiency in Python: Specifically focused on Data Science libraries (pandas, scikit-learn, NumPy, matplotlib/seaborn). Classic ML Expertise: Very good knowledge of Machine Learning algorithms (Regression, Classification, Clustering, Random Forests, Gradient Boosting) and solid model validation techniques. Data Manipulation Skills: You actually enjoy the 'dirty work' of data science—cleaning, wrangling, and structuring large datasets is second nature to you. SQL Mastery: Very good knowledge of SQL for data extraction and analysis. Consulting mindset: A business-oriented approach with the ability to present technical solutions to non-technical audiences. You are comfortable estimating time/budget and arguing for the best solution in a sales context. Workshop experience: Ability to actively participate in discovery workshops and cooperate with various stakeholders to manage changing priorities. Development environment: Familiarity with Jupyter Notebooks and Git. Language skills: Very good command of written and spoken Polish and English (C1 level). The Bonus (Nice to Haves): LLM Experience: Understanding of Large Language Models (GPT, Gemini, Claude), prompting, RAG, and fine-tuning. Software Engineering: Experience developing backend solutions, API integrations, or putting models into production code. Cloud Proficiency: Experience with AWS, Azure, or GCP. NLP Background: Experience with statistical learning techniques for Natural Language Processing (entity extraction, summarization, etc.). What do we offer? A proven track record: Join a team that has successfully completed over 40 AI projects in the last 8 years. We don't just talk about AI; we ship it. Innovation at the core: We develop our own open-source tools, such as drAIve—our proprietary framework for building LLM-based applications. You will have the chance to use it and contribute to it. Ambitious team: Work with a creative, talented, and highly experienced team of data scientists and engineers. Global impact: Contributing to innovative projects for clients all over the world. Flexibility: Flexible working hours and the possibility to work remotely.