Description
You will operate at the intersection of machine learning, engineering, and program execution, developing enough technical depth to understand how systems work end-to-end and how changes may impact teams across the organization. This role requires strong systems thinking, curiosity, and communication, with the ability to bring structure to ambiguous technical problems and influence teams toward shared outcomes.
Minimum Qualifications
5+ years leading complex technical programs related to AI/ML systems. Strong understanding of ML systems, software architecture, and technical dependencies across large-scale platforms. Track record of driving engineering roadmaps and execution across multiple teams and technical disciplines. Ability to engage credibly with engineers and technical leaders, ask effective technical questions, and identify risks beyond individual workstreams. Excellent written and verbal communication skills with technical teams and senior leadership. Demonstrated ability to learn complex technical domains quickly and operate independently in ambiguity.
Preferred Qualifications
Knowledge of ML workflows, frameworks, platforms, prediction systems, or algorithmic improvements. Background working with researchers or applied research teams to translate exploratory work into engineering execution. Familiarity with distributed systems, low-latency architectures, cloud platforms, or other large-scale systems. Background in advertising, ranking, recommendations, experimentation, or performance marketing systems. Demonstrated use of AI or automation to improve engineering or program-management workflows. History of influencing technical direction and challenging assumptions across teams without direct authority.
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