Machine Learning Engineer I - Message Security Products
Abnormal AI· Message Security Products
Hybrid (Singapore)full-timePosted 2mo ago
About the role
Abnormal AI is seeking a Machine Learning Engineer - I (MLE) to join the Misdirected Email Detection (MED) team. The role focuses on building practical, end-to-end ML solutions for misdirected email detection, balancing research ideas with production-grade systems to deliver reliable detection at scale and measurable customer impact in real-world environments.
Responsibilities
- Partner with Product Manager, Tech Lead and engineering stakeholders to align technical deliverables to roadmap milestones and ensure successful GA launches across supported environments.
- Own the full ML lifecycle for Misdirected Email, including data wrangling, feature engineering, model training and evaluation, deployment, and monitoring. Deliver iterative improvements with measurable reliability and customer impact.
- Run rigorous experiments and evaluations (offline metrics, online A/B testing, post-launch monitoring), set thresholds, and conduct targeted error analysis to prevent regressions.
- Communicate effectively across time zones, maintain high-quality technical documentation, and contribute to shared team knowledge.
- Participate in shared on-call rotation for owned components, with responsibilities focused on detection efficacy and realtime scoring systems. Priorities include resolving efficacy-related alerts, investigating high-visibility false positives, and addressing reported false positives/false negatives from customers or internal teams.
Qualifications
- BS degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a related engineering or quantitative field.
- 1+ years building and operating applied ML features in production systems.
- Proven experience contributing to end-to-end ML systems, including data wrangling (text and structured), feature engineering, model selection, training, evaluation, and production deployment with monitoring.
- Demonstrated ability to implement and reason about algorithms, develop features, average and combine signals, and apply numerical computing effectively.
- Demonstrated ability to interrogate production data, identify behavioral or trend shifts, and launch targeted experiments to improve model efficacy.
- Understanding of online vs offline pipelines, data tables and labeling workflows to effectively leverage tooling to support safe, scalable model deployments.
- Experience running offline metrics, online A/B tests, setting thresholds, and monitoring drift and performance, with guardrails and rollback strategies to ensure reliable iteration.
- Strong written and asynchronous communication skills. Effective working independently and across distributed, cross-functional teams.
Skills
Required:Data wrangling (text and structured)Feature engineeringModel training and evaluationProduction deployment
Last updated Aug 29, 2026. Interested? Apply on the company site.
About Abnormal AI
The Behavioral Security Platform for the AI era.
AI SecurityAbnormal Behavioral Security PlatformBehavioral SecurityEmail SecurityIdentity SecurityInsider ThreatPlatformenterprise-infrastructure
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