Research Engineer/Scientist – Cyber – ML

Research Engineer/Scientist – Cyber – ML

Requirements

• Deep domain expertise in cybersecurity, particularly in offensive security, vulnerability research, or cyber defense
• Hands-on keyboard offensive security experience including penetration testing, red teaming, or exploit development
• Experience with cyber threat characterization, risk assessment, or cybersecurity policy development
• Experience in applying ML to security problems, such as malware analysis or intrusion detection
• Familiarity with ICS/SCADA systems and critical infrastructure security
• Possession of security certifications such as SANS certifications, OSCP, or similar credentials
• Experience fine-tuning large language models for specialized domains
• Strong foundation in both security techniques and modern ML frameworks (PyTorch/TensorFlow)
• Experience translating complex technical findings into policy recommendations
• Ability to work with sensitive information while maintaining appropriate security protocols
• Experience with government cybersecurity programs or national security applications
• Ability to operate effectively in fast-paced environments while maintaining technical rigor
• Published research in relevant cybersecurity or AI security domains

Responsibilities

• Apply ML/AI research to build evaluation systems for cybersecurity safety, with focus on attack pattern characterization and threat detection
• Design and train specialized AI models for cyber threat classification, leveraging network data, exploit analysis, and attack protocols
• Work with SG research to design and implement state-of-the-art ML approaches for identifying dual-use cyber capabilities and zero-day exploits
• Build systems that target the transition of digital cyber capabilities into real-world attacks, preventing malicious exploitation
• Create and implement technical systems for monitoring emerging cyber threats and AI-enabled attack vectors
• Develop classifiers that can distinguish between legitimate security research and potential offensive cyber operations
• Build sophisticated evaluation infrastructure for measuring AI capability uplift in cybersecurity domains
• Design adversarial testing frameworks that probe model capabilities in cybersecurity contexts
• Integrate cyber range validation data with ML training pipelines to improve classifier accuracy
• Develop and maintain cyber threat datasets and benchmarks while ensuring appropriate information security
• Create tools that allow cybersecurity experts to quickly develop and deploy new threat detection evaluations
• Write production-quality Python code for high-throughput security data processing and evaluation systems
• Contribute to cyber risk assessments that directly inform AI model release decisions and policy development
• Work cross-functionally with cybersecurity policy experts, security researchers, and ML engineering teams

Preferred Qualifications

• Domain expertise in all specific risk areas is not required
• 100% of the skills needed to perform the job are not required
• Prior experience with AI model evaluation is not required