Applied ML Engineer - Email Security Detection

Abnormal Security Corp.; United States; Remote; USD 110,000 - 140,000; Full time

Job summary

Abnormal AI is seeking a Machine Learning Engineer I for the Misdirected Email Detection (MED) team to build practical, production-grade ML solutions that prevent misdirected outbound emails at scale.

You will own the full ML lifecycle—from data wrangling and feature engineering to training, evaluation, deployment, and monitoring—while collaborating with product, tech leads, and engineers to deliver measurable customer impact in real-world environments.

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.
• 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.

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.

Skills

Data wrangling

Feature engineering

Model training

Model evaluation

Production deployment

Experimental design

Numerical computing

End-to-end ML systems

Online vs offline pipelines

Education

BS degree in Computer Science, ML, AI, Information Systems, or related field

Job description

Abnormal AI is seeking a Machine Learning Engineer I for the Misdirected Email Detection (MED) team to build practical, production-grade ML solutions that prevent misdirected outbound emails at scale.

You will own the full ML lifecycle—from data wrangling and feature engineering to training, evaluation, deployment, and monitoring—while collaborating with product, tech leads, and engineers to deliver measurable customer impact in real-world environments.