Machine Learning Engineer

## About Incode Incode is the leading provider of world-class identity solutions that is reinventing the way humans authenticate and verify their identities online to power a world of digital trust. Through our revolutionary identity solutions, we are unleashing the business potential of universal industries including finance, government, retail, hospitality, gaming, and more, by reducing fraud and transforming human interactions with data, products, and services. We’re in the process of rapidly scaling our diverse global team and we’re looking for entrepreneurial individuals and leaders who are curious, driven, and excited by ownership to join a Unicorn-status scale-up! ## About Incode Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security. Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we’re scaling fast - and we’re looking for world-class Machine Learning Engineers to help us keep pushing the boundaries of biometric technology. ## The Impact You’ll Make As a Machine Learning Engineer at Incode, you’ll design, build, and deploy the deep learning models that power our most advanced technologies — from facial recognition and liveness detection to document processing and ID validation. You’ll join a highly specialized engineering team working on solving complex, real-world challenges with cutting-edge ML architectures. Your work will directly influence how people verify their identity safely, seamlessly, and securely around the world. ## What You’ll Own & Drive - **Innovate & Optimize** - Develop and refine state-of-the-art deep learning models for computer vision applications such as facial recognition, liveness detection, and document processing and validation. - **Production-Ready Solutions** - Architect and maintain scalable, efficient ML pipelines and ensure production-readiness and cost efficiency of deployed models. - **Research & Discovery** - Stay at the forefront of academic and industry breakthroughs, experiment with emerging architectures and algorithms, and translate research into production-grade solutions. - **Data Mastery** - Drive improvements in model performance through robust data preprocessing, cleaning, and analysis workflows. - **Collaborate & Communicate** - Partner closely with research, product, and engineering teams to integrate ML solutions seamlessly into Incode’s production environment. - **Mentorship & Leadership** - Provide technical guidance, share best practices, and contribute to building a culture of innovation and continuous learning. ## Your Background - 5+ years of industrial experience in Machine Learning, Deep Learning, or Computer Vision. - Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow. - Demonstrated experience developing, deploying, and optimizing models for both performance and cost efficiency in production environments (including edge AI). - Specialized expertise in at least one of the following areas: - Facial Recognition – face recognition, age estimation, facial attributes analysis. - Liveness Detection – liveness detection, anti-spoofing, 3D face modeling. - Document Processing – document analysis, OCR, ID validation, and data extraction. ## Nice to Have - Experience with cloud platforms such as AWS, GCP, or Azure. - Familiarity with DevOps practices and CI/CD pipelines. - Knowledge of privacy-preserving techniques such as federated learning or differential privacy. - Strong communication skills and ability to collaborate across teams. ## Benefits - Join a fast-growing unicorn with a mission to redefine digital trust. - Work on cutting-edge AI and biometric technologies with real-world impact. - Collaborate with a diverse and talented global team. - Opportunity to influence the future of identity verification and security.