Assist in the development of algorithms and models that handle complex visual challenges.
Build internal tooling to streamline dataset management, model versioning, and performance monitoring.
Maintain clean, well-documented codebases and participate in regular technical syncs with the US-based core team to ensure alignment on research goals.
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Decide where foundation models and LLMs stay in the loop, where dedicated trained heads take over, and where classical computer vision is the right answer.
Ship models into production: train, evaluate, package, deploy, and monitor. Partner with engineering and product to turn AI capability into customer-visible automation.
Hire and mentor the ML engineers who join after you.
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