Senior /Staff AI Engineer, Computer Vision

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. 

OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.

Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.

OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.

• Face intelligence & liveness detection — defenses against presentation attacks, injection attacks, and DeepFakes.
• Image & video quality assessment — reliable, security-critical decisions across diverse devices, environments, and network conditions.
• Document understanding & OCR — identity document parsing and FakeID detection for verification and compliance use cases.
• Multimodal risk & identity intelligence — fusing visual, behavioral, and contextual signals into identity-quality and trust signals.
• AI agents — applying agentic AI to scale investigation, detection, and operational defense.

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  Lead strategic AI initiatives: Drive the end-to-end design, training, and deployment of state-of-the-art deep-learning and multimodal models that scale to millions of users — spanning computer vision, vision-LLM, multimodal fusion, and AI-agent applications.
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  Architect scalable models & systems: Build and own production-grade AI pipelines for OCR / text extraction, biometric matching, fraud-pattern recognition, and AIGC generation/detection — engineered for low latency, high availability, and strong reliability.
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  Own face intelligence & liveness: Lead anti-spoofing capabilities against presentation, injection, and DeepFake attacks, and develop image/video quality models that keep security decisions reliable in real-world conditions.
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  Build identity & trust signals: Leverage user behavior, historical patterns, and cross-modal risk indicators to produce robust identity-quality and trust signals.
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  Drive execution & collaboration: Deliver high-quality, measurable results while managing ambiguity and prioritizing technical debt; partner with backend, product, infrastructure, risk, and compliance teams to integrate AI into large-scale systems, and influence stakeholders across technical and non-technical backgrounds.
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  Advance applied R&D: Drive experimentation in vision-LLM, multimodal representation learning, and AI agents; stay current with academic and industry advances and translate them into practical, production-ready defenses.
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  Elevate the technical bar & mentor: Provide technical guidance and mentorship, set a high engineering standard, and democratize applied-AI best practices across the team and the wider organization.

• 8+ years of hands-on experience developing AI/ML solutions in areas such as computer vision, AI agents, multimodal learning, vision-LLM, or generative video/image modeling — including significant experience deploying AI/ML systems into production.
• Deep AI/ML expertise: Strong proficiency with PyTorch and/or TensorFlow, and solid experience with large-scale production ML systems.
• Strong technical & coding skills: Strong coding ability (e.g., Python) and the system-level thinking to design end-to-end AI solutions with high availability and low latency.
• Technical leadership: Demonstrated ability to lead complex, cross-team technical initiatives and deliver impactful AI solutions at scale.
• Strategic communication: Strong communication and leadership skills, with experience influencing technical direction across engineering, product, and leadership teams.
• Mentorship: A proven track record of mentoring senior engineers and raising the technical bar.
• Education: Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field.

• Experience in identity verification, KYC/KYB, AML, fraud detection, biometric security, or media forensics.
• Hands-on experience with OCR, document parsing, fake-ID detection, or document-security systems.
• Familiarity with real-time / low-latency AI systems and large-scale production deployment.
• Knowledge of modern data and AI/ML infrastructure (e.g., Spark, Flink, Kafka, Airflow, Snowflake).
• Familiarity with MLOps best practices — monitoring, retraining, and continuous improvement of production models.
• Experience working in fast-paced technology companies or security-critical environments.
• Research publications, patents, or open-source contributions in relevant AI fields.