Work closely with the Head of AI, product managers, and engineers to develop and deliver AI-driven security features.
Design, train, and deploy machine learning models used to detect malicious traffic patterns, bots, and anomalies in web traffic.
Build and maintain ML pipelines for data collection, training, evaluation, and deployment.
Work primarily in Python, using common ML frameworks and data tooling to train and optimize models.
Integrate ML models into real-time security systems such as WAF and behavioral analytics engines.
Improve data quality, feature engineering, and training workflows to increase model accuracy and reliability.
Monitor model performance in production and retrain models as new data and threat patterns emerge.
Collaborate with data, infrastructure, and product teams to ensure scalable and reliable ML systems.
Communicate findings and model outcomes clearly to both technical and non-technical stakeholders.

3+ years of experience as an ML Engineer, Data Scientist, or similar role working with production ML systems.
Strong Python skills with experience using ML libraries such as PyTorch, TensorFlow, or scikit-learn.
Experience building data pipelines and model training workflows.
Good understanding of classification, anomaly detection, and behavioral modeling.
Experience working with large datasets and SQL-based data systems.
Familiarity with deploying ML models into production environments.
Understanding of software engineering best practices such as version control, testing, and CI/CD.
Degree in Computer Science, Engineering, Mathematics, or related field.

Machine Learning Engineer

Key skills