A leading technology company is looking for an Android Malware Researcher to join its research team. In this role, you will conduct in-depth malware research and reverse engineering, investigate malicious Android applications, identify emerging threats and attack techniques, and contribute to the development of detection and analysis capabilities. You will work hands-on with malware samples, combining static and dynamic analysis, reverse engineering, programming, and threat research to uncover malicious behavior and better understand the evolving Android threat landscape.
Responsibilities: Conduct in-depth research and reverse engineering of Android malware Perform static and dynamic analysis of malware samples and Android applications Investigate malicious behavior, attack techniques, and emerging malware trends Identify and document new Android threats and attack vectors Develop detection rules and automated processes for identifying and analyzing malware Use reverse engineering, debugging, and instrumentation tools to analyze complex samples Document research findings and contribute to technical threat intelligence reports Collaborate with other researchers and share knowledge across teams
Requirements 3+ years of proven experience in research, reverse engineering, or low-level development in Android, Windows, macOS, or Linux environments Strong experience with reverse engineering and malware analysis Proficiency in at least one programming language such as Java, Python, JavaScript, or C/C++ Hands-on experience with reverse engineering tools and decompilers such as JADX, JEB, IDA Pro, or Ghidra Familiarity with instrumentation or debugging tools such as Frida, GDB, or LLDB Good understanding of networking fundamentals and common protocols Strong analytical and problem-solving skills Ability to work independently as well as collaboratively in a research-oriented environment Valid international government-issued photo ID (e.g., a current passport or international driver's license) for identity verification and global client interaction