About
ERGO Technology & Services S.A. (ET&S), a member of the Munich Re and ERGO Group, delivers integrated IT and business services to international markets. Their expertise lies in providing advanced IT services, with a focus on modern, business-driven technology solutions. On the business side, they also support the Group in various end-to-end insurance processes, including finance, operations, and underwriting. With offices in Warsaw and Gdansk, and strong global partnerships, they foster a dynamic, multicultural environment that promotes diversity and international opportunities.
Responsibilities
•Preparing and analysing data from various sources to develop and optimise (Agentic) AI and machine learning models
•Design and standardise effective, scalable AI environments, AI blueprints and processes
•Designing, implementing and operating software solutions for the use of structured and unstructured data, particularly in the area of (Agentic) AI and machine learning, with the aim of achieving a highly automated ML lifecycle
•Developing technical know-how, tools and methods for (Agentic) AI
•Supporting operational units in implementing AI models into existing processes and systems to maximise the value of (Agentic) AI
•Designing and pilot AI solutions for monitoring and evaluating the outcomes of executed and implemented use cases, in order to measure the effectiveness of AI initiatives
Requirements
•Fluency in English and German
•Completed degree in computer science, artificial intelligence, data
•Sound knowledge of GenAI, machine learning and deep learning, including relevant algorithms and models, as well as RAG
•Experience in preparing, cleansing and enriching data for use in AI applications
•Very good knowledge of one or more programming languages (preferably Python), particularly with respect to AI frameworks (e.g. PyTorch); knowledge of database programming languages such as SQL for managing and querying data
•Experience with tools, frameworks and technologies for training, deploying and monitoring AI models, including MLOps practices
•Familiarity with distributed systems and cloud platforms for scaling AI applications (e.g., Azure, Databricks and Kubernetes)
•Strong ability to identify and analyse data patterns and to develop models for prediction and decision-making
•Ability to think and work in a networked manner, to collaborate with interdisciplinary teams, and to communicate complex technical concepts in an understandable way
•Strong service orientation, excellent teamwork skills and a high level of commitment to meeting the needs of business units and advancing the development of AI solutions
•Familiarity working in a team, using git, able to create proper pull requests and perform code reviews
Benefits
•Medical package, sports card, and numerous sports sections
•Flexible working hours
•Confidential employee assistance program
•Possibility of remote working
•Numerous workshops and training courses
•Hackathons and meetups for sharing expertise
•Wide range of digital learning platforms and language courses
•Participation in CSR activities each year
•Company-wide bike races and soccer matches, film marathons in the cinema room and other team-building activities
