Senior Machine Learning Engineer, Compliance

About The Opportunity

Building ML systems for compliance at a crypto exchange is a different kind of problem from most ML engineering work. The data spans on-chain transactions, fiat flows, KYC records, and behavioural signals that very few organisations have in one place. The problems are genuinely unsolved, the stakes are high, and the work has direct bearing on how a global exchange detects and responds to financial crime. For someone who wants their engineering work to matter beyond model accuracy metrics, this is an interesting place to be.

This role sits within a team of data scientists, analytics engineers, and compliance specialists who are building the analytical and AI infrastructure that powers the compliance function. You will work across the full ML lifecycle, from feature pipelines and model development through to deployment and monitoring, with close involvement from the domain experts who understand what the models need to do in practice.

AI-assisted development is how this team works. LLM-assisted coding, automated analytical pipelines, and AI-powered investigation tooling are part of the daily workflow. We are looking for engineers who already operate this way and who can raise the bar for what that looks like in a production compliance environment.

What You’ll Be Doing

• Design, build, and deploy ML models for compliance use cases including AML transaction monitoring, customer risk rating, KYC/KYB risk scoring, sanctions exposure detection, and SAR analytics, working closely with data scientists on model architecture and with data engineers on pipeline design.

• Own the production infrastructure for compliance ML: feature pipelines, model serving, monitoring, drift detection, and retraining workflows. Models in a compliance context need to be reliable, auditable, and well documented, and you will be responsible for making sure they are.