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CDR (Amsterdam - Cedar), Netherlands
Onsite
This role was originally published on 28 May 2026.
Think Forward! Our goal is to help people advance in life and business. We are a well-established brand with strong financials, global reach, and omni-channel strategies. If you value innovation, agile principles balanced with compliance and quality, reliable service, and a practical work approach, this is the place for you.
What department?
Within Wholesale Banking Advanced Analytics (WBAA), the Discovery team is a fast-paced group that partners with different areas of ING’s Wholesale Bank to explore, shape and validate AI opportunities.
Goal is to define, validate and prioritize the most impactful AI opportunities for WB, making the most efficient use of our limited resources. During the idea gathering we check on business impact, re-use, scalability and strategic fit. The ideas with highest potential and priority will move to an AI discovery phase, where they will be evaluated for desirability, viability, and feasibility.
We help stakeholders clarify problems, assess data and technical feasibility, and create rapid prototypes that demonstrate business value. Successful initiatives are then prepared for build and enable ING’s Wholesale Banking teams.
Role description
As an ML/AI Engineer in WBAA Discovery, you turn ambiguous business questions into feasible analytics solutions. You work end-to-end: from problem framing with stakeholders, to data exploration and feasibility assessments, to rapid proofs of concept and prototypes, and finally to clear recommendations and handover packages for build teams.
You thrive in a start-up mindset: short feedback loops, iterative delivery, and making pragmatic trade-offs while staying aligned with banking standards (risk, privacy, security and model governance). Success in this role depends on strong stakeholder management, clear communication, and comfort with uncertainty, ambiguity, often working with incomplete requirements and evolving priorities.
Do you recognize yourself in this profile:
Strong Python programming proficiency
Demonstrated expertise in AI integration, including working with large language models (LLMs) such as Gemini and Claude, implementing retrieval-augmented generation (RAG) patterns, designing and evaluating prompts, and utilizing vector databases.
Ability to explore data quickly and assess feasibility (data availability/quality, constraints, and expected business impact).
Data engineering skills: building scalable data pipelines and optimising data processing (e.g., Spark, Airflow, partitioning, incremental loads, performance tuning).
Experience building rapid prototypes/PoCs and translating outcomes into clear recommendations and next steps.
Experience designing and deploying cloud solutions, including CI/CD, containerisation (e.g., Docker) and infrastructure-as-code (e.g., Terraform).
Experience with production-minded development (testing, monitoring/observability, reliability), even when starting from early-stage prototypes.
Experience with APIs and service-based architectures (microservices, REST/gRPC, async programming).
Strong stakeholder management: ability to align multiple parties, manage expectations, and communicate complex topics to technical and non-technical audiences.
Comfortable with rapidly changing priorities of varying degrees of certainty; you proactively structure problems and drive decisions with limited information.
Collaborative mindset: work effectively with data engineers, analysts, data scientists and product owners in a fast-paced discovery setting.
Nice to have (but Not Required): Even if you don't meet every requirement, we encourage you to apply. Experience in these areas is a bonus:
ML model training, validation, and experiment tracking experience
GCP expertise
Familiarity with discovery process or design sprints; strong story-telling and visualisation skills to drive alignment.
Experience with Kubernetes and container platforms (e.g., OpenShift).
Experience building and maintaining high-load APIs and OpenAPI integration/governance.
Basic networking knowledge and familiarity with event-driven architecture.
Experience working in regulated environments.
Familiarity with agentic frameworks (ADK, LangChain, LangGraph, CrewAI) and multi-agent design patterns is a plus.
Basic understanding of Java/Kotlin for connectivity to ING internal systems.
Contribution to open-source projects is considered advantageous.
Rewards and benefits
We want to make sure that it’s possible for you to strike the right balance between your career and your private life. Find out more about our employment conditions.(opens in new window)
The benefits of working with us at ING include:
25-28 vacation days depending on contract
Pension scheme
13th month salary
8% Holiday payment
Hybrid working
Personal growth and challenging work with endless possibilities
An informal working environment with innovative colleagues
About us
Curious about how ING empowers people and businesses to move forward?
Discover what we do and what we can offer you(opens in new window).
Questions?
Please visit our Frequently Asked Questions(opens in new window) section to find some answers on questions you might have.
Contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation letter by clicking the ‘Apply’ button.