AI Engineer
NICE
| Company | NICE |
| Category | Engineering |
| Location | Netherlands - Alkmaar |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 8 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. So, what’s the role all about?
Join us in shaping the future of financial market compliance. We're investing in a new AI capability at our R&D group in Alkmaar, and we're looking for an AI Engineer to help build it from the ground up.
Our goal: build world-class AI models that help compliance officers sleep well at night — AI they can trust, and AI that gives them proof. To get there, we're investing in serious infrastructure (including dedicated high-end GPUs) and, more importantly, in the experts who know how to make the most of it. If you want to help shape this future and change the world of communication, market, and trade surveillance — we'd love to hear from you.
How will you make an impact?
Co-found and shape our new AI engineering team in NiCE Netherlands — you'll influence architecture, tooling, and culture from day one
Train and fine-tune LLMs, SLMs, and other ML/DL models for compliance use cases such as communication surveillance, market surveillance, and trade surveillance
Architect training pipelines that integrate cleanly with our data capture platforms
Optimize inference pipelines to deliver AI capabilities cost-efficiently at scale
Evaluate emerging AI techniques (RAG, agents, distillation, fine-tuning strategies, etc.) and bring the most promising ones into production
Own explainability and auditability end-to-end — from choosing the right interpretation technique (SHAP, attention analysis, custom audit trails) to producing model cards and evidence artefacts that satisfy compliance officers and regulators. This is a first-class engineering concern here, not an afterthought.
Have you got what it takes?
MSc or PhD in Computer Science, AI/ML, or a related field — or equivalent hands-on experience
Solid experience with modern ML/DL frameworks (PyTorch, TensorFlow, Hugging Face)
Experience training and/or fine-tuning LLMs or SLMs
Strong NLP foundations applied to real-world problems — for example: sequence classification, named entity recognition, semantic search, or RAG over unstructured financial communications. Familiarity with the quirks of financial and regulatory text (abbreviations, jargon, high-stakes edge cases) is a plus
Familiarity with ML infrastructure: training pipelines, GPU clusters, MLOps
Pragmatic mindset — you care about getting models into production, not just into notebooks
Bonus: experience in financial services, RegTech, or any highly regulated domain
What’s in it for you?
A rare opportunity to help build a new AI engineering team from day one
Access to dedicated high-end GPU infrastructure for model training and experimentation
A rock-solid data platform (NTR-X) on which to run your models
Competitive salary and strong benefits package
Personal development budget for training, conferences, and certifications
A dynamic, international company with a collaborative team culture
Hybrid working: 2 days in the office, 3 days from home
Meaningful work on systems used by some of the world's largest financial institutions
Enjoy NiCE-FLEX!
At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.
About the Team
We're an energetic, technically-minded team of software builders based in Alkmaar. Our belief: AI-First is AI-Proof — meaning that the teams who embed AI deeply into how they build and operate will be the ones wh