Hybrid Principal Detection Engineer

at Hewlett Packard Enterprise

• Job title: Principal Detection Engineer
• Job type: Full Time
• Experience level: Lead
• Salary: $117,500 - $270,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Cyber Security, Google Cloud Platform, Java, Python, PyTorch, Scikit-Learn, SQL, Tensorflow, Go
• Location requirements: Hybrid, Spring, United States

About the role

• Principal Detection Engineer developing advanced threat detection systems using ML/AI technologies at HPE. Collaborating with cybersecurity teams to enhance threat detection strategies.

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.
• Stay up to date with emerging threats, ML/AI technologies, and advancements in cybersecurity to continuously improve detection systems.
• Maintain clear documentation of models, processes, and methodologies for knowledge sharing across teams.

Requirements

• Bachelor’s or master’s degree in computer science, cybersecurity, data science, or related engineering field.
• Certifications such as CISSP, CISM, CEH or OSCP preferred.
• Proven experience (8+ years) in cybersecurity, with a focus on threat detection and response.
• Deep understanding of cybersecurity frameworks and concepts, including attack vectors, threat landscapes, and defense mechanisms.
• Familiarity with SIEM/SOAR/ and EDR/XDR platforms.
• 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).

Benefits

• Health & Wellbeing
• Personal & Professional Development
• Unconditional Inclusion