Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
Agentic AI @ 4
Agentic Systems
Azure @ 4
Databricks @ 4
GenAI
Generative AI @ 4
LLM
MLOps @ 4
Machine Learning @ 4
PyTorch @ 6
Python @ 6
Spark @ 4
scikit-learn @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Shape how AI transforms the banking industry by designing, developing, and bringing AI-powered solutions into production within ABN AMRO's Enterprise Enabling Data Domain. The role involves working with modern tooling, large and complex datasets, and cloud-based platforms to create scalable solutions that deliver business value.
Responsibilities
- Design, train, and evaluate advanced machine learning, generative AI, and LLM-based solutions.
- Explore and apply complex datasets, metadata structures, knowledge graphs, and unstructured data.
- Develop scalable, production-ready AI products using Azure, Databricks, and Spark.
- Translate business questions into AI opportunities and communicate insights clearly.
- Experiment with generative AI, agentic systems, vector-based retrieval, and automated model development.
- Collaborate with Machine Learning Engineers, Data Engineers, Data Analysts, and Domain Experts to embed AI into business and IT processes.
- Advise stakeholders on responsible AI, data quality, explainability, and model governance.
- Work within a cross-functional team of Data Scientists and Machine Learning Engineers supporting stakeholders across the I&T organisation and beyond.
Requirements
- 5+ years of experience.
- Proven experience with machine learning, LLMs, and generative or agentic AI.
- Hands-on experience with Azure Machine Learning, Databricks, and Spark.
- Proficiency in Python and modern ML/AI libraries and frameworks, such as PyTorch and scikit-learn.
- Experience with MLOps, model deployment, monitoring, and automated pipelines.
- Experience with innovation-driven projects involving emerging AI techniques.
- Up-to-date knowledge of modern AI/ML research, tooling, and best practices.
- Strong stakeholder management and advisory skills.
- Ownership mindset and a commitment to high-quality, production-ready solutions.
- Understanding of responsible AI principles, fairness, transparency, and governance.
- Experience working with big data ecosystems.
- Fluent in English.
- Ability to work in a multicultural and interdisciplinary environment.
Benefits
- Salary scale 11 of €6,066–€8,666 per month.
- Personal development budget of €1,000 per year.
- Flexible and hybrid working options.
- Public transportation pass or travel budget.
- Opportunity to work with leading AI technologies in a modern data environment.
- Responsibility for owning solutions end to end.
- Excellent employment conditions and extensive internal career opportunities.
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