Machine Learning Engineer I - Message Security Products

Abnormal AI
Singapore
Workplace: RemoteFull timeFunction: Data Science & Machine LearningExperience: 1+ yearsEducation: bachelorsSkills: ["Written communication","Asynchronous communication","Independent work","Cross-functional collaboration","Technical documentation"]

Build and iterate end-to-end machine learning solutions for misdirected email detection, helping prevent accidental data loss at scale. Own the full ML lifecycle—data wrangling, feature engineering, training and evaluation, deployment, and monitoring—while running offline and online experiments (A/B testing) and conducting error analysis to avoid regressions. Collaborate across teams, document work, and participate in an on-call rotation focused on detection efficacy and real-time scoring.

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FursaFursa
Abnormal AI
Abnormal AI
1 month ago

Machine Learning Engineer I - Message Security Products

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and iterate end-to-end machine learning solutions for misdirected email detection, helping prevent accidental data loss at scale. Own the full ML lifecycle—data wrangling, feature engineering, training and evaluation, deployment, and monitoring—while running offline and online experiments (A/B testing) and conducting error analysis to avoid regressions. Collaborate across teams, document work, and participate in an on-call rotation focused on detection efficacy and real-time scoring.
Location: Singapore
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Entry level

Key Responsibilities

  • •Partner with Product Manager, Tech Lead, and engineering stakeholders to align technical deliverables to roadmap milestones and support GA launches.
  • •Own the full ML lifecycle for misdirected email detection, from data wrangling and feature engineering through deployment and monitoring.
  • •Run rigorous experiments and evaluations using offline metrics and online A/B testing, setting thresholds and performing error analysis to prevent regressions.
  • •Communicate across time zones and maintain high-quality technical documentation while sharing team knowledge.
  • •Participate in on-call rotation for owned components, focusing on detection efficacy, resolving efficacy-related alerts, and investigating false positives/false negatives.

Key Requirements

  • •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: data wrangling (text and structured), feature engineering, model selection, training, evaluation, and production deployment with monitoring.
  • •Ability to implement and reason about algorithms, develop features, and apply numerical computing to combine/average signals.
  • •Experience with online vs offline pipelines and running experiments (offline metrics, online A/B tests), setting thresholds, and monitoring drift and performance with guardrails.
Experience:1+ years
Education:Bachelor's
Skills:Written communicationAsynchronous communicationIndependent workCross-functional collaborationTechnical documentation
Languages:English
Tech Stack:PythonGoAWSSparkDatabricks

Company Brief

Abnormal AI
Provides AI-powered email security and human behavior analysis to detect phishing, business email compromise, and account takeover attacks. The platform helps organizations protect employees and communications across cloud email and collaboration tools.
Industry: Cybersecurity
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Headquarters: San Francisco, United States
Founded: 2018
WebsiteLinkedIn