At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions.
Our culture is what makes that possible: we play to win, we obsess over quality, and we win as One Moss, and it works.
Moss closed a €35 million Series C in August 2026, crossing a €1 billion valuation, and became one of Europe's fintech unicorns.
Join us for what's next.
We’re expanding our Data & AI team and looking for a senior/lead contributor who has hands-on LLM app/agent experience and is fluent in classical ML.
You’ll own end-to-end LLM/ML initiatives - from problem framing and modeling to evaluation, deployment, and iteration - directly improving core product workflows (invoice understanding, approval matching, reconciliation, anomaly detection, and user-assist).
Your responsibilitiesOwn LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.
Define evaluation & monitoring: gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.
Productionize with Platform/Data Eng: bring your models live and iterate/improve until they are adopted by your stakeholdersAbout you5-10+ years in applied ML with production ownership of shipping models/systems.
Hands-on LLM app/agent experience (tool use/function calling, RAG, structured outputs, guardrails) in production.
Strong Python + ML stack (e.
, scikit-learn, XGBoost/LightGBM, PyTorch/TF) and solid experiment/evaluation.
You rigorously validate assumptions, identify root causes, and prioritize solving the right problem before building.
End-to-End Executor: You independently own projects from ideation to production, balancing model performance with engineering realities.
You ensure solutions are scalable, monitored, and maintained with thoughtful evaluation, deployment, and iteration strate.