About the Role
The role involves developing scalable machine learning models to identify anomalies and attacks in application traffic. The engineer will work on improving detection accuracy, reducing false positives, and integrating models into production systems.
Responsibilities
- Design and implement machine learning algorithms for threat detection
- Optimize model performance across large-scale datasets
- Collaborate with security researchers to define detection logic
- Train and evaluate models using real-world attack data
- Improve system accuracy by refining feature engineering
- Deploy models into production environments securely
- Monitor model behavior and adapt to new attack patterns
- Reduce false positive rates through iterative tuning
- Work with distributed systems handling high-volume traffic
- Integrate machine learning pipelines with existing infrastructure
- Conduct experiments to validate model effectiveness
- Maintain documentation for models and training processes
- Support incident investigations using model outputs
- Ensure compliance with data privacy standards
- Participate in code reviews and system design discussions
Nice to Have
- Prior work on intrusion detection systems
- Experience with API security concepts
- Knowledge of OWASP Top Ten vulnerabilities
- Familiarity with containerization and orchestration tools
- Contributions to open-source machine learning projects
- Research publications in security or ML domains
- Experience mentoring junior engineers
Benefits
- Health and wellness coverage
- Paid time off and holidays
- Professional development stipend
- Remote work equipment allowance
- Flexible work schedule
- Performance-based bonuses
- Stock options program
- Mental health support services
- Team retreats and virtual events
- Inclusive and diverse work culture
Compensation
Competitive salary with performance-based bonuses
Work Arrangement
Remote position with flexible hours
Team
Collaborative engineering team focused on AI-driven security solutions
Technology Stack
Python, TensorFlow, PyTorch, Scikit-learn, Kafka, AWS, Docker, Kubernetes, Prometheus, Grafana
Security Focus
Models trained on real attack traffic, emphasis on zero-day detection, integration with WAF and API gateway systems
Available for qualified candidates
