Risk AI Data Scientist
At a glance
Mid-level AI Research role at ING. Warszawa · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build agentic AI workflows for risk use cases, using ADK
- Track generative AI outputs for hallucinations, quality issues and drift
- Turn documents, PDFs and OCR data into signals and usable features through NLP pipelines
- Fine-tune open-weight models on GCP GPUs to capture credit and financial risk requirements
- Write production-ready Python for models, workflows and application components
What you bring
- Strong Python skills for AI work, including experience with PyTorch or TensorFlow
- You have built applications powered by LLMs and agentic AI workflows
- Practical experience with Google Cloud tools such as Vertex AI, Workbench or ADK
- You have managed structured and unstructured data, including text and numerical information
- A master's degree in computer science, mathematics or economics
Who this fits
This role suits a hands-on AI practitioner building and monitoring production solutions for credit risk modelling. The work spans exploration, deployment and scaling, with a focus on unstructured data and banking risk use cases. It is based in Warsaw, Poland.
From the employer
ING Hubs Poland is hiring!
The expected salary for this position: 13000 – 22000 PLN
The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.
We are looking for an AI Engineer to drive the integration of advanced AI capabilities into the bank’s overall risk management (out of which Credit risk model maintenance is one of them).
In this role, you work on advanced AI solutions (LLM-powered apps, dedicated fine-tuned models, regular Machine Learning, Agentic AI workflows) in risk management domain (credit risk modelling). You will not only build and steer these solutions; you will help design the cognitive layer of the bank’s risk management environment, turning cutting-edge AI into production-ready, compliant solutions.
We are looking for you, if you have:
- Advanced Python practice in AI solutions (including PyTorch/TensorFlow experience)
- Hands-on experience in building LLM-powered applications and Agentic AI workflows
- Experience in manipulating and governing structured and unstructured textual and numerical data
- Practical knowledge of Google Cloud Platform (Vertex AI, Workbench, ADK)
- Strong experience with Azure DevOps / GitHub ops
- Experience with end-to-end pipelines (data → model → deployment)
- Master’s degree in computer science, mathematics or economics
You'll get extra points for:
- Experience working in Agile/Scrum teams
- Experience in software engineering
- Hands-on with transformers architecture and model fine-tuning
- Knowledge on AI (risk) governance
Your responsibilities:
- Design and implement agentic AI workflows (ADK) for risk domain
- Evaluate and monitor GenAI systems in this context (e.g. hallucinations, quality, drifting)
- Work with large-scale unstructured data (documents, PDFs, OCR) as a core part of the role
- Build NLP pipelines to extract complex signals (e.g. transaction patterns, legal clauses) from unstructured text and convert them into usable features
- Prototype custom models by fine-tuning open-weights models (e.g., Llama, Mistral) on GCP GPUs to understand the specific nuances of risk management in wholesale/retail banking, credit policies, and financial risk (exploration, production and scaling)
- Write clean, modular, production-ready Python code for models, workflows and application components.
Information about the Team:
The mission of Integrated Risk is focused on providing risk identification, aggregation and insight capabilities at Group level across the various Risk domains. The team department is using those capabilities across the various risk functions, to assume a general oversight of risk governance, policies and frameworks, and to steer group-wide model and implementation activities across locations.
The Bank-wide Credit Risk Models department is responsible for the management of Wholesale Banking (WB) IRB and IFRS9 and the Bank-wide Credit Risk Economic Capital models — including their development, monitoring, and advisory support to the business — in cooperation with relevant stakeholders. All the models in scope are groupwide, managed and developed centrally and consistently applied across all ING’s locations.
The role naming convention in the global ING job architecture will be "Data Scientist IV".