Android Malware Researcher

Why Join Us?

Join our dynamic Mobile Detection Engines and Protections Team and play a critical role in safeguarding millions of mobile users from sophisticated cyber threats. We are seeking an experienced and passionate Android Malware Researcher to conduct deep-dive analyses, leverage AI-driven methodologies, uncover emerging threats, and innovate robust defenses to reinforce Check Point’s leadership in global cybersecurity.

Key Responsibilities

• Analyze complex Android malware, applications, SDKs, and obfuscated code to identify malicious behaviors.
• Conduct in-depth reverse engineering of Android APKs using advanced static and dynamic analysis techniques.
• Develop internal security tools and automation frameworks to enhance malware detection and streamline analysis processes.
• Collaborate on designing and implementing detection signatures, machine learning models, AI-driven methodologies, and proactive threat mitigation strategies.
• Engage in building, training, and deploying AI models that enhance detection capabilities and predictive analytics.
• Work closely with software developers, data scientists, and threat intelligence experts to continuously improve detection accuracy and responsiveness.
• Participate in high-profile global investigations of mobile threat campaigns.
• Lead applied research initiatives for innovative detection engines targeting Android and iOS platforms.
  
  

• Strong presentation skills, rapid comprehension, and the ability to clearly explain complex issues and cases in simple terms.
• Demonstrated expertise in reverse engineering Android applications using tools such as JEB, JADX, IDA Pro, or equivalent.
• Hands-on proficiency with dynamic analysis frameworks like Frida, Xposed, Magisk, or similar tools.
• Deep understanding of Android OS internals, APK structure, and protection methods.
• Solid familiarity with Java and Python, with experience supporting research through scripting or tool development; C/C++ experience is advantageous.
• Experience utilizing network analysis tools (e.g., Wireshark, Burp Suite, MITM Proxy).
• Familiarity with malware classification, threat intelligence, or signature development is highly beneficial.
• Previous exposure or experience in developing or leveraging AI/ML models for cybersecurity applications is strongly preferred.
  
  

• Passionate about cybersecurity with a keen interest in malware research and mobile threats.
• Excellent analytical and problem-solving skills; meticulous attention to detail.
• Self-motivated, organized, and capable of independent research.
• Strong team orientation with excellent communication and collaboration abilities.