• Aesthetic Evaluation Metrics: Define and implement the "eyes" of the system, quantitative metrics that correlate with human perception of quality, brand alignment, and engagement.
• The Optimization Loop: Build the backend architecture that uses performance data to finetune Vision-Language Models (VLMs) in real-time, effectively creating a self-improving creative engine.
• Generative Experiments: Design the technical framework for testing thousands of creative variations against one another, discovering novel patterns in what makes an ad successful.

• The Scientist-Engineer: You are as comfortable reading a research paper on VLMs as you are writing production Python code. You prefer problems that don't yet have a Stack Overflow answer.
• Domain Translator: You have a deep background in AdTech (creative optimization, ranking, or relevance) and can translate abstract marketing goals (like "brand lift") into concrete loss functions and engineering constraints.
• Curiosity: You are fascinated by the intersection of art and algorithm.

Compensation