About the company
We are an implementation and consulting company. We specialize in areas such as IT rescue, digital transformation, and maintenance. Together, we create state-of-the-art digital solutions, primarily for clients in healthcare, banking, insurance, e-commerce, FMCG, and retail. We combine innovation with a practical approach to solving technological problems. Our team is made up of IT enthusiasts who value growth, modern technologies, and a friendly work environment.
Responsibilities
•Acting as a trusted technical advisor to clients — solving complex machine learning challenges and guiding them through the process of practical system implementation.
•Designing the architecture and implementing multi-step workflows based on Agentic AI.
•Delivering tailored production solutions in collaboration with clients, partners, and product teams.
•Designing and building data pipelines and infrastructure for distributed machine learning and recommendation systems.
•Implementing MLOps solutions, including data validation, model monitoring, and lifecycle management in a production environment.
•Creating and optimizing ETL/ELT processes in analytics environments and data warehouses.
•Creating dedicated scripts and software to support advanced artificial intelligence and ML systems.
Requirements
•At least 7 years of hands-on experience working with recommendation systems, data pipelines, or distributed machine learning.
•Practical experience in machine learning (ML), artificial intelligence (AI), technical consulting, and customer service.
•Knowledge of programming and scripting languages such as Python, Perl, C, C++, or Java.
•Experience with Vertex AI, MLOps, Document AI, and Generative AI.
•Experience building multi-step Agentic AI workflows using ADK, Agent Engine, LangChain, and AgentSpace.
•Understanding of the practical aspects of deploying ML models to production (feature extraction and definition, data validation, monitoring, and model management).
•Knowledge of deep learning and ML frameworks such as TensorFlow, PyTorch, or XGBoost.
•Knowledge of data warehouse architecture, ETL/ELT processes, and analytics environments (Apache Beam, Hadoop, Spark, Hive).
Conditions
•Work on client projects and proprietary products
•Real influence on business and technology solutions within the projects being delivered
•Training and support in defining a career development path
•Company events, access to medical services, and sports packages
•Employment under a B2B contract
•Remote/hybrid work (Warsaw)
•A short recruitment process
