AI Engineer

OChK is a leading cloud services provider in Poland with extensive experience in advanced data analytics, artificial intelligence, and cybersecurity solutions. They develop scalable and secure environments on their proprietary OChK Platform as well as cloud platforms of strategic partners Google and Microsoft. Their comprehensive services include strategy, migration, IT environment management, application and data/AI solutions development, optimization, automation, security, and regulatory compliance support. Their clients include nearly 400 organizations across various sectors such as public institutions, private companies, corporations, supervised entities, and startups.

• Minimum 2 years of practical experience as an AI Engineer, MLOps Engineer, or Data Scientist working on production solutions.
• Practical knowledge of Generative AI, RAG architecture, Prompt Engineering, fine-tuning, and frameworks such as LangChain, CrewAI, ADK, AutoGen, and Semantic Kernel.
• Strong proficiency in Python and standard ML stack (PyTorch, NumPy, Pandas, Scikit-learn).
• Practical experience with Google Cloud or Azure services in data and AI domains.
• Familiarity with development best practices including Git, Docker, Kubernetes, CI/CD, and REST APIs.
• Excellent command of Polish and English (spoken and written).

Nice to have:

• AI/ML cloud certifications (e.g., Google Cloud Professional ML Engineer, Microsoft Certified: Azure AI Engineer Associate).
• Experience working with vector databases (ChromaDB, Pinecone, Qdrant, Pgvector).
• Experience in regulated sectors such as finance, banking, or healthcare.

• Analyze client needs in the context of ML/AI project implementation.
• Translate business requirements into AI solution architectures and support consulting and architecture teams.
• Design and support the creation, deployment, and scaling of applications based on Generative AI, LLM, RAG, and traditional Machine Learning.
• Utilize native AI/ML services on Google Cloud (Vertex AI) and Microsoft Azure (Azure OpenAI / Azure AI Services).
• Build and automate data pipelines, training, evaluation, deployment, and monitoring of production models.
• Design, build, and automate evaluation processes for AI/ML applications.
• Support internal organizational processes in adopting AI tools and solutions.
• Monitor latest AI trends, test new models and frameworks, and optimize cost and performance of deployments.