Senior AI Algorithm Specialist – Computer Vision & Media Integrity

3. Key Responsibilities
· Deepfake Innovation: Design and refine state-of-the-art generative architectures (GANs, Diffusion Models, Transformers) for facial reenactment and latent space manipulation.
· Liveliness & Security: Develop industry-leading Presentation Attack Detection (PAD) systems to identify 3D masks, digital injections, and high-resolution replay attacks.
· Adversarial Research: Play both sides of the "AI arms race"—building tools to find vulnerabilities in biometric systems so you can architect the systems that can't be fooled.
· Optimization & Scale: Implement high-performance Computer Vision (CV) pipelines for real-time inference on both high-end cloud clusters and edge devices.
· Mathematical Rigor: Apply custom loss functions and gradient optimization to solve complex artifacts in synthetic video.

4. Required Qualifications & Technical Profile
· Academic Background: PhD or MS in Computer Science, Mathematics, or a related field with a heavy focus on Deep Learning and Computer Vision.
· Framework Mastery: Expert-level proficiency in PyTorch or JAX (CNNs, Vision Transformers, and Optical Flow).
· Domain Expertise: Vast experience with Deepfake frameworks (e.g., DeepFaceLab, FaceSwap) and biometric science (texture analysis, depth estimation).
· Anti-Spoofing Experience: Proven success in implementing rPPG (remote photoplethysmography) and other non-intrusive liveliness detection methods.
· Deployment Skills: Experience with NVIDIA TensorRT, ONNX, and Quantization-Aware Training for high-speed deployment.