Malware Reverse Engineer - AI Trainer

We are looking for experienced cybersecurity professionals to join our team to help train AI models. In this role, you will evaluate AI-generated security content, solve technical cybersecurity problems, and provide feedback to improve how AI systems reason about real-world threats and defenses. Cybersecurity platforms are increasingly powered by AI, but these systems still require practitioners with real-world experience to validate their outputs. You will work directly with advanced AI models to assess their accuracy, strengthen their reasoning, and contribute to building more reliable tools for the cybersecurity industry. Benefits This is a full-time or part-time REMOTE position You’ll be able to choose which projects you want to work on You can work on your own schedule Projects are paid hourly starting at $40+ USD per hour Work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand Responsibilities Evaluate AI-generated cybersecurity content, including threat analysis, vulnerability assessments, and offensive security techniques Design and solve security-focused technical problems used to train AI systems Write clear technical explanations and security-relevant code Provide feedback that directly shapes the next generation of AI security models Qualifications 2+ years of hands‑on experience in cybersecurity (e.g., penetration testing, red teaming, incident response, detection engineering, DFIR, malware analysis, threat intelligence, or similar) Some coding experience required Fluency in English (native or bilingual level) Strong writing and analytical skills A bachelor’s degree is preferred Cybersecurity certifications are a plus (e.g., OSCP, CRTO, GREM, GCFA, CEH) Notes To get started, you will complete a short assessment. If successful, you will gain access to paid work through our platform. Payment is made via PayPal. We will never ask for any money from you. This role is only available to candidates in the US, Canada, UK, Ireland, Australia, and New Zealand. #cybersecurity #J-18808-Ljbffr DataAnnotation