Machine Learning Engineer II - Message Security Products

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October 29

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Abnormal Security

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Abnormal provides total protection against the widest range of attacks including phishing, malware, ransomware, social engineering, executive impersonation, supply chain compromise, internal account compromise, spam, and graymail.

501 - 1000 employees

📋 Description

• Partner with PM, TL, EM and UTL to align technical deliverables to roadmap milestones and ensure successful GA launches across supported environments • Own the full ML lifecycle for MEP, including data wrangling, feature engineering, model training and evaluation, deployment, and monitoring. Delivering 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. Priorities include resolving efficacy-related alerts, investigating high-visibility false positives, and addressing reported false positives/false negatives from customers or internal teams

🎯 Requirements

• BS degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a related engineering or quantitative field • 3+ years building and operating applied ML features in production systems • Proven experience building end-to-end ML systems, including data wrangling (text and structured), feature engineering, model selection, training, evaluation, and production deployment with monitoring • Demonstrate ability to implement and reason about algorithms, develop embeddings, average and combine signals, and apply numerical computing effectively • Demonstrate ability to interrogate production data, identify behavioral or trend shifts, and launch targeted experiments to improve model efficacy • Display 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.

🏖️ Benefits

• Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.