# ML Engineer

**Company:** [Kodex](https://hotfix.jobs/companies/kodex)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $150k – $180k/yr
**Experience:** 4+ years
**Skills:** Machine Learning, Classification, Anomaly Detection, Clustering, Feature Engineering, Model Evaluation, Drift Monitoring, Data Pipelines, Databricks, AWS
**Posted:** 2026-06-04

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

## Job Description

## 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

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**Apply:** https://hotfix.jobs/jobs/a13ed017-a90c-42d2-82ce-7bf484fa0609
**Canonical:** https://hotfix.jobs/jobs/a13ed017-a90c-42d2-82ce-7bf484fa0609