AI Engineer: Computer Vision
Zyphe · New York, NY, USA
Pay
Not listed
Setting
On-site
About Zyphe Zyphe is building agentic compliance for regulated fintechs, crypto exchanges, and enterprises. Our five-agent system (Document, Liveness, Name Resolution, Risk Profile, Historical) automates KYB, KYC, and AML while a privacy-first architecture means personal data never has to live on our customers' servers. We are early, focused, and shipping. Real customers, real revenue, an active fundraise with a committed lead. The next twelve months are about turning that into a defended category position. About the role Zyphe is hiring an AI Engineer specializing in computer vision to design and deploy real-time visual intelligence systems at the core of our identity verification platform. This is not a research-only seat. You will own the full lifecycle, from model prototyping to production deployment, building the perception layer that powers face detection, liveness checks, and document verification. Responsibilities Design and train computer vision models for face detection, liveness verification, and document analysis. Build and optimize real-time inference pipelines using PyTorch, TensorFlow, ONNX Runtime . Deploy models to edge and cloud with low-latency constraints ( TensorRT, CoreML ). Develop data augmentation and synthetic data strategies to improve model robustness. Build evaluation frameworks and monitor model drift in production. Integrate CV models into the verification pipeline with backend engineers. Implement privacy-preserving techniques (on-device processing, federated approaches). Maintain MLOps for training, versioning, and deployment. You may be a good fit if you Have strong experience building and deploying computer vision models in production. Have deep knowledge of CNN and transformer architectures for vision tasks. Have hands-on PyTorch or TensorFlow plus model optimization toolchains. Have experience with edge deployment (ONNX, TensorRT, CoreML or similar). Have solid MLOps practice: experiment tracking, CI/CD for models, monitoring. Are familiar with face detection, recognition, or document processing pipelines. Have strong Python and comfort with cloud infrastructure (AWS / GCP). Can reason about privacy implications of visual data processing. Strong candidates may also have experience with Face anti-spoofing, liveness detection, or presentation-attack detection. ID document analysis (MRZ, hologram, tamper detection). On-device or browser-based inference (WebAssembly, MediaPipe, CoreML). Privacy-preserving CV and confidential computing. Synthetic data generation for face or document datasets. Annual salary Competitive, commensurate with experience. Equity included. Logistics Location: Remote. Hybrid policy: Fully remote, with periodic on-sites for offsites and key meetings. Visa sponsorship: Not available at this time. Education We require at least a Bachelor's degree in a related field, or equivalent professional experience.
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