Red Team Engineer

Required

• 4+ years of experience in offensive security, adversarial ML, AI red teaming, or ML engineering with a strong adversarial focus.
• Hands-on experience generating synthetic media — voice cloning and TTS, face swap, lip-sync, diffusion-based image and video tools — in an offensive or research context, not just reading about it.
• Strong Python skills and practical ML fluency (PyTorch or similar): you can build attack tooling, automate testing pipelines, and reason about why a model fails, not just that it did.
• Working knowledge of adversarial ML techniques — evasion, adversarial perturbations, compression and post-processing attacks, data poisoning — and how to measure model robustness.
• Clear communicator who can turn technical findings into prioritized, actionable guidance for engineers and non-technical audiences alike, and who thrives with ambiguity and minimal supervision.
• Background in media forensics, signal processing, speech/audio, or computer vision. (nice to have)
• Traditional red team or penetration testing experience (cloud, APIs, web), relevant certifications (e.g., OSCP), or familiarity with AI security tooling such as Garak, PyRIT, or the Adversarial Robustness Toolbox. (nice to have)
• Published research, conference talks, CVEs, or open-source contributions in adversarial ML, deepfakes, or AI security. (nice to have)
• Within 1 month, you'll...
• Get up to speed on our detection model architecture across modalities, the current red team program, test harnesses, and adversarial dataset.
• Meet your AI, Data, Product, and Security counterparts to understand how findings are triaged and remediated today.
• Reproduce a set of recently released generative tools and techniques and run them against our production models.