Shape the Future of Cybersecurity with Us Are you driven by deep curiosity, bold innovation, and the desire to transform cutting-edge AI research into real-world cybersecurity impact? Join Cynet, an established yet rapidly growing cybersecurity startup, where you’ll help build next-generation AI-powered security products from the ground up. You’ll be part of a small, elite, cross-disciplinary team working closely with security researchers, R&D engineers, data engineers, and product leaders.
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.
Requirements: * 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.
* Background in offensive research or deep endpoint security.
* Experience with generative models, agentic reasoning, or building LLM-based AI systems.
* Familiarity with cloud security, DevOps tooling, or MLOps practices.
This position is open to all candidates.