The company is seeking a security research engineer to deconstruct complex threats and build next-generation detection systems, leveraging generative AI, LLMs, and agentic systems to automate and scale detection and analysis capabilities.
Requirements
- demonstrated experience in leading machine learning projects in malware domain or detection systems, including a strong understanding of model development, data preprocessing, and deployment.
- Proven experience in the complete software development lifecycle, with proficiency in one or more programming languages (e.g., Python, Go, C++).
- Strong experience in reverse engineering, system security, threat research, malware/code analysis or vulnerability research is a big plus
- Demonstrated experience in leading machine learning projects, including a strong understanding of model development, data preprocessing, and deployment is a plus
- Solid understanding of the threat landscape, including common attack vectors, malware techniques, and threat actor tactics is a plus.
Responsibilities
- Lead end-to-end machine learning projects for threat detection.
- Design, build, and deploy innovative security solutions leveraging Generative AI and agentic systems.
- Develop intelligent agents and workflows to automate threat hunting, accelerate malware analysis, and streamline threat intelligence processes.
- Disseminate cutting-edge research findings and contribute to the security community by publishing results in technical blogs, industry white papers, and academic papers, particularly on topics related to malware analysis and AI for security.
- Work closely with cross-functional teams, including other security services: threat prevention, internet security and IoT security, endpoint security to integrate and deliver sustainable and quality coverage and defense.
Other
- 6+ years of experience in a research or engineering role
- A proven track of top tier publications in cybersecurity related areas is a big plus.
