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1Kosmos is seeking an AI/Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions for identity security and authentication. The role spans the full ML lifecycle—from dataset creation and model training through deployment and optimization—with a focus on real-world production systems.
Key responsibilities include designing and implementing AI models for image classification, object detection, OCR, and feature extraction. You'll develop real-time image quality assessment and capture guidance algorithms, create and maintain data pipelines for collecting and labeling datasets, and implement model optimization techniques for both mobile on-device and cloud inference. The role involves applying fraud detection methods to identify tampering, forgeries, and replay attacks in visual data, integrating ML models into production APIs and mobile SDKs, and continuously monitoring and improving model performance.
You'll collaborate closely with product and engineering teams to align AI capabilities with business objectives. The company is building passwordless identity solutions trusted by leading global brands, combining decentralized identity protocols, FIDO2-certified cryptography, and NIST-compliant biometric systems.
Required qualifications include a Bachelor's or Master's degree in Computer Science, AI/ML, or related field (or equivalent experience), plus 3+ years building and deploying ML models in production. You must be proficient in Python and ML frameworks (PyTorch, TensorFlow, or similar), experienced with computer vision libraries (OpenCV) and OCR technologies, and have strong understanding of deep learning architectures for image and text recognition. Familiarity with cloud platforms (AWS, GCP, Azure) and API development is essential. The role is based in the NJ/NY area with a hybrid working model.
Preferred qualifications include experience with model quantization and mobile optimization, synthetic data generation, security/liveness detection, compliance regulations (GDPR, CCPA), and open-source ML contributions or published research.
