Machine Learning Engineer II - Behavioral Security Products

Stack

Responsibilities

• ▹Contribute to the development of machine learning algorithms and models for behavioral modeling and cybersecurity attack detection
• ▹Work with cross-functional teams to understand requirements and translate them into effective ML solutions
• ▹Conduct exploratory data analysis, feature engineering, model development, and evaluation
• ▹Work with infrastructure and product engineers to productionize models and new ML-based features
• ▹Monitor and improve production models through feature engineering, rules, and ML modeling as part of a team effort
• ▹Participate in code reviews to ensure the quality and maintainability of ML systems
• ▹Stay updated on the latest research in machine learning, data science, and AI
• ▹Adopt and contribute to the development of machine learning best practices within the organization

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 like pandas, scikit-learn, and 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 to answer business questions and assess system efficacy
• ▹Ability to communicate technical ideas in a clear, non-technical manner

Nice to have

• ▹Familiarity with LLMs
• ▹Previous experience in cybersecurity
• ▹Previous 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)

Soft skills