Machine Learning Engineer I
Abnormal Security2 months ago
Remote, SingaporeEntry Level
Responsibilities
- Partner with product, technical leadership, and engineering stakeholders to align deliverables with roadmap milestones and support GA launches.
- Own the full ML lifecycle for Misdirected Email Detection, including data wrangling, feature engineering, model training, evaluation, deployment, and monitoring.
- Run offline evaluations, online A/B tests, post-launch monitoring, threshold setting, and targeted error analysis to prevent regressions.
- Translate research ideas into production-grade, scalable detection systems and deliver iterative improvements with measurable customer impact.
- Maintain technical documentation and contribute to shared team knowledge across distributed teams.
- Participate in on-call rotation for owned components, investigating efficacy alerts and customer or internal false positives and false negatives in real-time scoring systems.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a related engineering or quantitative field.
- At least 1 year of experience building and operating applied ML features in production systems.
- Experience with end-to-end ML systems, including data wrangling, feature engineering, model selection, training, evaluation, production deployment, and monitoring.
- Ability to implement and reason about algorithms, develop features, combine signals, and apply numerical computing.
- Experience analyzing production data, identifying behavioral or trend shifts, and launching targeted experiments to improve model efficacy.
- Understanding of online and offline pipelines, data tables, and labeling workflows for safe and scalable model deployments.
- Experience with offline metrics, online A/B tests, threshold setting, drift and performance monitoring, guardrails, and rollback strategies.
- Strong written and asynchronous communication skills and ability to work independently across distributed, cross-functional teams.
- Experience with Python, Go, AWS, Spark, and Databricks is preferred.
- Experience in email security, data loss prevention, misdirected email prevention, customer-focused ML deployments, detector or rule development, or operationalizing research into reliable customer-facing systems is preferred.
Tech Stack
Categories
About Abnormal Security
Abnormal Security builds an AI-based cloud email and SaaS security platform for enterprises, preventing phishing, business email compromise, and account takeover. Its products integrate natively with Microsoft 365, Google Workspace, and other business apps, delivered as a subscription service. Founded in 2018 and headquartered in Las Vegas, Nevada, the privately held company focuses on securing large organizations’ email and connected applications.