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.

📌 Adaptive Machine Learning Researcher (Toronto)
🏢 Adaption
📍 Toronto