Shape adaptive algorithms with Python and deep learning frameworks while exploring real-time learning, feedback, and model efficiency. This Modelling Resident role focuses on building intelligence that continuously adapts to the world. You will co-design algorithms responding to product signals and feedback. The work spans model efficiency, synthetic data, interfaces, real-time alignment, and algorithmic optimization. Key Responsibilities:
Build algorithms that continuously learn and adapt Co-design real-time responses to product signals Explore stronger methods for capturing feedback Optimize across software, hardware, and algorithms Measure value through real-world product impact Requirements:
Computer science degree or equivalent research experience Project experience touching model efficiency or related areas Systems thinking across the full machine learning stack Robust Python and PyTorch, JAX, or TensorFlow skills Familiarity with RLHF and fine-tuning techniques Apply adaptive algorithms, systems thinking, Python, and deep learning expertise to continual intelligence research and development.