Found Description
You won’t just build models—you’ll own how intelligence shows up in real products. This role sits at the intersection of data, engineering, and decision-making, where models aren’t experiments—they’re expected to perform, scale, and deliver measurable impact.
Key Responsibilities
- Design, develop, and deploy scalable machine learning models across production environments
- Translate ambiguous business problems into structured ML solutions with clear success metrics
- Own end-to-end ML pipelines—from data ingestion and feature engineering to model deployment and monitoring
- Work closely with data engineers to ensure high-quality, reliable data pipelines
- Optimize models for performance, latency, and cost in real-world environments
- Continuously evaluate model performance and retrain pipelines based on drift or evolving data
- Collaborate with product and business teams to align ML outputs with decision-making need...
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