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Abnormal AI, a Series D-funded cybersecurity leader (Gartner Magic Quadrant Leader for Email Security, $5.1B valuation, 100% YoY ARR growth), is seeking a Machine Learning Engineer II to join the Account Takeover Detection team. The team protects Fortune 500 customers against account takeover attacks using behavioral AI systems.
In this role, you will contribute to developing machine learning algorithms and models for behavioral modeling and cybersecurity attack detection. You'll work cross-functionally to translate customer requirements into effective ML solutions, conduct exploratory data analysis and feature engineering, develop and evaluate models, and collaborate with infrastructure and product engineers to productionize ML-based features. You'll monitor and improve production models through feature engineering, rules, and ML modeling, participate in code reviews, and stay current with the latest research in machine learning and AI.
The Account Takeover Detection team's mission is to leverage cutting-edge ML technologies for proactive detection and prevention of account takeover attempts, continuously improving capabilities to stay ahead of evolving fraud patterns. This role offers the opportunity to contribute significantly to the team's charter, direction, and roadmap by defining technical goals, addressing customer problems, maintaining production models, and ensuring operational excellence.
Requirements:
- Proven experience as a Machine Learning Engineer or similar role in a commercial environment (3+ years)
- Knowledge of machine learning algorithms, statistics, and predictive modeling
- Proficiency with Python and machine learning toolkits (pandas, scikit-learn, optionally PyTorch/TensorFlow)
- Awareness of machine learning operations (MLOps) and productionization of ML models best practices
- Familiarity with building data and metric generation pipelines using tools like SQL or Spark
- Ability to communicate technical ideas in a clear, non-technical manner
Nice to have:
- Familiarity with LLMs
- Previous experience in cybersecurity
- Experience with Airflow or similar ML pipeline orchestration tools
- Experience with large-scale ML systems and data infrastructure
- Previous experience in behavioral modeling techniques
- PhD or equivalent proven experience in ML research
- Familiarity with cloud computing platforms (AWS, Azure)
