Machine Learning Engineer II - Behavioral Security Products

Role overview A mid-level machine learning engineering role on an Account Takeover Detection team within a behavioral cybersecurity product organization. The team applies machine learning to proactively detect and prevent account takeover attempts, staying ahead of evolving fraud patterns. The role contributes meaningfully to charter, direction, and roadmap while maintaining production models and upholding operational excellence.

Responsibilities - Contribute to developing machine learning algorithms and models for behavioral modeling and attack detection. - Partner with cross-functional teams to translate requirements into effective ML solutions. - Conduct exploratory data analysis, feature engineering, model development, and evaluation. - Work with infrastructure and product engineers to productionize models and ship new ML-based features. - Monitor and improve production models through feature engineering, rules, and ongoing modeling work. - Participate in code reviews to uphold quality and maintainability of ML systems. - Track the latest research in ML, data science, and AI, and help evolve ML best practices across the organization.

Requirements - 3+ years as a Machine Learning Engineer or similar role in a commercial environment. - Solid grasp of ML algorithms, statistics, and predictive modeling. - Proficiency in Python and ML toolkits such as pandas and scikit-learn, with optional experience in PyTorch or TensorFlow. - Working knowledge of MLOps and best practices for productionizing ML models. - Familiarity with building data and metric generation pipelines using SQL or Spark to answer business questions and assess system efficacy. - Ability to communicate technical ideas clearly to non-technical audiences.

Nice to have - Familiarity with LLMs. - Prior cybersecurity experience. - Experience with Airflow or similar ML pipeline orchestration tools. - Background with large-scale ML systems and data infrastructure. - Experience with behavioral modeling techniques. - PhD or equivalent proven experience in ML research. - Familiarity with cloud platforms such as AWS or Azure.