Machine Learning Engineer

• 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
• 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

Benefits

• Meaningful Equity
• Flexible Working Hours & Workplace
• Open Vacation Policy
• Wellness Program
• International Travel Opportunities
• Additional benefit package according to location (401k, medical insurance, etc.)- Demonstrated experience developing, deploying, and optimizing models for both performance and cost efficiency in production environments (including edge AI)
• Liveness Detection – facial authentication, anti-spoofing, and anti-deepfake defense
• Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow
• Proven ability to design and maintain end-to-end ML pipelines
• Excellent communication and collaboration skills across cross-functional teams
• Facial Recognition – face recognition, age estimation, facial attributes analysis
• Document Processing – OCR-based extraction, document analysis, and quality assurance
• 5+ years of industrial experience in Machine Learning, Deep Learning, or Computer Vision
• Passion for mentoring talent and thriving in both long-term research and rapid iteration cycles
• Specialized expertise in at least one of the following areas:
• ID Verification – biometric data authentication and document integrity validation
• Track record of research contributions or publications in deep learning and computer vision
• Strong analytical thinking balanced by practical execution
• Deep curiosity and technical excellence in AI and computer vision
• Collaborative spirit and ability to simplify complex ideas for diverse audiences
• Commitment to innovation, scalability, and continuous improvement
• Builder mindset with a drive to deliver real-world impact through applied research