Machine Learning/AI Engineer

Translate ambiguous business problems into well-defined ML/DS tasks, then set technical direction for ML initiatives using tradeoffs like cost, latency, and complexity. Own ML systems end-to-end in production—data ingestion, training, serving, monitoring, retraining, and rollback—while designing for failure modes such as drift and feedback loops. Build and ship model-powered services and APIs, define evaluation metrics (offline and A/B), and partner with product and design to drive business impact.