Here, you’re not just joining a company, you’re stepping into a place where you can envision, build, and deploy foundational AI technologies that protect organizations worldwide. You will have the rare opportunity to drive innovation end-to-end, shape our future technology, and create AI systems that make a real difference in defending against modern cyber threats.
This is a role for someone who wants to put their soul into their craft, someone hungry to learn fast, experiment boldly, and turn ambitious ideas into production-ready AI solutions.
What will you do:
* Drive innovation by combining deep security research with modern AI techniques to build impactful, customer-facing security capabilities.
* Build and refine intelligent generative AI agents that drive automated cybersecurity reasoning, investigation workflows, and threat analysis.
* Extend and enhance our next-generation AI antivirus engine by designing new feature representations, building file parsers, and developing ML models end-to-end.
* Engineer and implement core parser and model components in C++ and Python to seamlessly integrate into the Cynet Endpoint Agent and platform infrastructure.
* Use Cynet’s ML experimentation pipelines to run experiments, optimize performance, and deliver production-ready detection models.
* Serve as the cybersecurity expert within the Data Science team, guiding threat modeling, malware understanding, and security-driven AI design decisions.
About Us:
Cynet is a leader in threat detection and response, designed to simplify security for organizations of all sizes. Our mission is to empower lean security teams and their partners with an AI-powered, unified platform that autonomously detects, protects, and responds to threats – backed by 24×7 security experts. With a Partner First mindset , we focus on helping customers and partners stay protected, operate confidently, and achieve their goals. Our vision is to give every organization true cybersecurity peace of mind, providing fast, accurate protection without the noise or complexity.
* 5+ years of hands-on cybersecurity research experience.
* Proven experience working with EDR , malware analysis, threat detection, and security tooling.
* Proficiency in C, C++, and Python with strong debugging abilities.
* Solid understanding of Windows internals , including low-level OS concepts.
* Experience with static and dynamic analysis , reverse engineering, and real-world threat investigations.
* A scientific, data-driven approach to problem-solving, from ideation through experimentation and production.
* Strong understanding of statistical concepts and ML feature engineering techniques.
* Experience analyzing large-scale datasets using SQL, Spark, or similar tools.
Preferred / Nice to Have
* Certifications or academic background in Data Science / Machine Learning / AI
* Experience with ML frameworks and experimentation environments.
* Experience with generative models, agentic reasoning, or building LLM-based AI systems.
* Familiarity with cloud security, DevOps tooling, or MLOps practices.
