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KodexKodexUnited States

ML Engineer

Build and deploy production ML models and pipelines to detect suspicious activity, improve verification accuracy, and support threat intelligence workflows.

150k – 180k/yr
Remote4+ YOEML Engineering

About the role

What You’ll Do

  • Build and deploy models to detect and flag suspicious behavior (classification, anomaly detection, clustering, ranking)
  • Own ML pipelines end-to-end (feature generation, training, evaluation, batch/streaming inference, backfills, versioning)
  • Design evaluation + monitoring: ground truth strategies, offline metrics, drift monitoring, alerting
  • Collaborate with product & engineering to integrate intelligence into user-facing workflows (review queues, decision-support tooling)
  • Improve data quality and accessibility (schemas, lineage, reproducibility, access controls)
  • Contribute to operational rigor: runbooks, incident response, safe rollout practices

Requirements

  • 4+ years building software ML systems in production
  • Experience in fraud, abuse, trust & safety, risk, or security analytics
  • Experience with modern ML/DS workflows: experimentation, evaluation, deploying models other teams rely on
  • Comfortable with data pipelines and messy real-world data (instrumentation gaps, bias, label noise, changing definitions)
  • Focus on reliability and safety (rollbacks, guardrails, human-in-the-loop review, auditability)
  • Clear cross-disciplinary communication; turn ambiguous investigative needs into scoped engineering work
  • Pragmatic approach: know when to start with baseline vs. invest in stronger modeling/infra

Nice-to-Haves

  • Familiarity with LLMs / RAG / agentic workflows for internal tooling or decision support
  • Experience in compliance-sensitive environments (privacy, access controls, audit trails)

Stack

  • Core: TypeScript, Node.js, Postgres, AWS
  • Data: Databricks
  • AI capabilities across document processing, internal tooling, automation

Skills

Machine LearningClassificationAnomaly DetectionClusteringFeature EngineeringModel EvaluationDrift MonitoringData PipelinesDatabricksAWS

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