AI/ ML /Llm Engineer

Kyotu Technology is a boutique software house based in Wrocław and Warsaw, working fully remotely or in hybrid mode across Poland. They focus on long-term, high-quality engineering and building complex, production-grade systems with real business impact. Their teams have real influence on technical and architectural decisions.

Must haves:

• Minimum 4 years of experience in AI / ML engineering
• Strong Python skills and experience with data/ML libraries (e.g. NumPy, Pandas)
• Experience in building and evaluating machine learning models
• Experience with LLMs and GenAI use cases (e.g. prompt engineering, RAG, LLM pipelines)
• Experience or strong interest in agentic AI systems (multi-step workflows, tool usage, autonomous agents)
• Experience with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
• Understanding of data processing, feature engineering, and model evaluation
• Experience with experimentation tools (e.g. MLflow, Weights & Biases)
• Ability to work across research and production environments
• High level of independence, curiosity, and problem-solving mindset
• Good communication skills and team orientation
• English at B2 level

Nice to have:

• Experience with reinforcement learning (e.g. PPO, SAC, TD3)
• Experience with optimization tools (e.g. PuLP, Pyomo)
• Experience with advanced forecasting methods (e.g. Prophet, LightGBM, Transformers)
• Familiarity with LLM orchestration frameworks (e.g. LangChain, LlamaIndex)
• Experience with vector databases (e.g. Pinecone, Weaviate, FAISS)
• Experience with cloud platforms (e.g. AWS, Azure, GCP)
• Experience with MLOps practices and CI/CD for ML

• Collaborate on upcoming projects involving AI, ML, and LLM systems
• Work on applied AI combining machine learning, optimization, and modern LLM-based systems
• Contribute to use cases across automation, data processing, intelligent systems, and AI-driven product development
• Engage with agentic AI systems, working at the intersection of classical ML and generative AI
• Participate in projects involving forecasting, optimization, reinforcement learning, and LLM-powered workflows including autonomous or semi-autonomous agents