Optimize machine learning systems across software and hardware while applying Python, deep learning, and full-stack systems thinking.
As a Modelling Resident, you will pursue system-wide efficiency gains across software, hardware, and algorithmic domains. Your work connects model optimization with real-world product impact. Relevant projects may involve synthetic data, interfaces, real-time alignment, or algorithmic optimization.
Key Responsibilities: Drive efficiency gains across complete technical systems
Collaborate across software, hardware, and algorithmic domains
Develop algorithms reacting to real-time feedback
Investigate current approaches to product signal capture
Connect algorithm quality with real-world impact
Requirements: Computer science degree or equivalent engineering experience
Systems thinking across the full machine learning stack
Strong Python programming ability
Experience with PyTorch, JAX, or TensorFlow
Familiarity with RLHF and model fine-tuning
Bring cross-stack optimization, Python, and deep learning framework experience to systems shaping efficient, continually adapting intelligence.