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Job Description
- Develop shared algorithmic frameworks and foundational math in core modeling domains, including runtime behavior steering, latent-space pattern detection, optimization loops, and fine-tuning rooted in industry best practices.
- Streamline engineering efforts across global product lines by shifting fragmented, application-specific pipelines into cohesive, highly scalable, and reusable platform layers.
- Architect definitive, automated evaluation methodologies and standardized benchmarking metrics to provide scientifically rigorous validation models, eliminating manual execution overhead.
- Serve as a technical conduit between product, data science, applied engineering groups, machine learning research organizations, and centralized core infrastructure teams.
- Act as a strategic advisory partner to executive engineering leadership on platform maturity, long-term technical debt reduction, and operational capacity across technical workstreams.