Machine Learning Systems Optimization Resident

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 systemsCollaborate across software, hardware, and algorithmic domainsDevelop algorithms reacting to real-time feedbackInvestigate new approaches to product signal captureConnect algorithm quality with real-world impactRequirements:
Computer science degree or equivalent engineering experienceSystems thinking across the full machine learning stackStrong Python programming abilityExperience with PyTorch, JAX, or TensorFlowFamiliarity with RLHF and model fine-tuningBring cross-stack optimization, Python, and deep learning framework experience to systems shaping efficient, continually adapting intelligence.
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