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
Solid 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.