The DNS Security Research team is responsible for delivering high quality content to our products to prevent successful cyberattacks, with a special focus on DNS security, network security, privacy protection, etc. We design, build, and maintain various detection systems and data infrastructures to protect customers against constantly evolving threats and attacks.
Requirements
- Expertise in DNS and DNS security;
- Good knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Trees, Logistic Regression, Deep Learning, and Boosting;
- Familiar with large-language models (LLMs) and experience to leverage them to address cybersecurity threats;
- Excellent programming skills in Python, Shell script, Go, or SQL;
- Understanding of core network protocols (TCP/IP, HTTP/HTTPS, etc.);
- Knowledge and experience with modern databases and big data tools, such as MySQL, MongoDB, Elasticsearch, Redis, BigQuery;
- Experience with malware traffic analysis is a plus;
Responsibilities
- Track and research emerging threats and innovate new ways to identify malicious indicators used by malware and attacks, including domains, URLs, IP addresses, sha256, email addresses, etc.;
- Design and build scalable and extensible prevention/detection systems;
- Leverage data-driven approaches, such as statistical analysis, machine learning, and other advanced techniques;
- Convert research results and discoveries into products, research papers, etc.
Other
- BS/MS in Computer Science or related fields with security research experience; PhD in Cyber Security or Machine Learning is a plus.
- Creative thinker and team player.
- Have great passion and be highly self-motivated in data-driven security research;
- Be comfortable working independently, efficiently;
- Excellent communication (written and verbal) and presentation skills;
