Strong foundation in Deep Learning and sequence modelling, with experience applying them to real-world problems
Deep knowledge in Handwriting Recognition, Handwriting Synthesis, Document Layout Analysis and/or related areas
Research track record via publications and/or open-source contributions in Document AI or relevant fields
Strong grasp of computer science fundamentals with a robust background in software engineering
Proficiency in Python and at least one Machine Learning framework such as PyTorch, TensorFlow and JAX
Working knowledge of C++, Rust or Swift (a plus)
Knowledge of model optimization for on-device deployment
Excellent communication skills in English
Responsibilities
Research and develop state-of-the-art AI/ML models to serve millions of users
Push the boundaries of document analysis and recognition technologies, such as Handwriting Recognition, Handwriting Synthesis, Stroke Classification and Document Layout Analysis
Collaborate closely with a multidisciplinary team, including engineers, QA, and product designers, in a fast-paced environment to deliver features rapidly