Hewlett Packard Enterprise (HPE) is seeking a Principal Cyber Detection Engineer to strengthen its detection engineering program, scale detection coverage, increase alert fidelity, and reduce mean time to detect by developing and implementing advanced threat detection systems using ML/AI.
Requirements
- Strong expertise in Machine Learning (ML) and Artificial Intelligence (AI), including model design, training, and deployment.
- Knowledge of adversarial machine learning and techniques for defending against model exploitation.
- Experience with anomaly detection, behavioral Modeling, and predictive analytics in cybersecurity contexts.
- Experience with deep learning architectures or natural language processing (NLP) applied to cybersecurity.
- Experience integrating machine learning models into security operations workflows in enterprise environments.
- Proficiency in languages such as Python, Go, SPL, YaraL, R , Java, SQL and frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience with big data technologies and cloud environments (AWS, Azure, GCP).
Responsibilities
- Design, develop, and implement advanced threat detection systems leveraging ML/AI techniques to identify malicious activity, anomalies, and emerging risks.
- Build and optimize machine learning models for real-time detection, including supervised, unsupervised, and reinforcement learning approaches.
- Data engineering and pre-processing for cybersecurity applications. Analyze large-scale datasets to extract meaningful insights, detect patterns, and enhance the accuracy of detection systems.
- Develop and refine detection algorithms for intrusion detection, anomaly detection, endpoint security, behavioral analysis, and other cybersecurity applications.
- Automate detection workflows and processes to improve efficiency and scalability of security monitoring systems.
- Work closely with threat intelligence, red team, security operations, and data scientists, to integrate detection models into security platforms and tools.
- Test, validate, and monitor the performance of detection models, ensuring reliability and minimizing false positives/negatives.
Other
- This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.
- Proven leadership experience in shaping detection strategies and guiding cross-functional efforts.
- Your experience enables you to explain complex technical issues to non-technical audiences, and you have a track record of mentoring and technical leadership.
- Certifications such as CISSP, CISM, CEH or OSCP preferred.
- Familiarity with regulatory requirements and compliance frameworks (e.g., GDPR, NIST, ISO 27001).
