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.