We’re hiring an ML Engineer to join Kodex’s Verifications / Threat Intel org and help build the intelligence layer that protects our platform — detecting suspicious activity, improving verification accuracy, and turning messy real-world signals into scalable, auditable systems.
This role sits at the intersection of product, data, and security. You’ll partner closely with Threat Intel operators and engineers to translate investigative workflows into production-grade models, pipelines, and decision-support tooling. You’ll also help evolve our current approach beyond noisy, brittle heuristics toward systems that are measurable, explainable, and safe to operate.
You’ll work across the full lifecycle — from problem framing and data exploration through deployment, monitoring, and iteration. Example areas include:
Build and deploy models to detect and flag suspicious behavior (classification, anomaly detection, clustering, ranking, and other approaches as appropriate)
Own ML pipelines end-to-end (feature generation, training, evaluation, batch/streaming inference, backfills, and versioning)
Design evaluation + monitoring: ground truth strategies with Threat Intel, offline metrics, drift monitoring, and alerting
Collaborate with product & engineering to integrate intelligence into user-facing workflows (e.g., review queues, and decision-support tooling)
Improve data quality and accessibility by working with data engineering patterns (schemas, lineage, reproducibility, and access controls)
Contribute to operational rigor: runbooks, incident response, and safe rollout practices for systems that impact customer trust
You Might Be a Fit If You...
Have 4+ years of experience building software ML systems in production
Experience in fraud, abuse, trust & safety, risk, or security analytics
