Machine Learning Engineer
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About this role
POWER A WORLD OF TRUST
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.
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