Tech Stack

Description

You will lead modeling strategy for content understanding (vision, NLP, multimodal), design and ship production models that generate content signals used across multiple product surfaces, and own the full ML lifecycle from data strategy to monitoring. Collaborate with infrastructure and signal-consuming teams to ensure scalable, reliable training and serving.

Requirements

• MS/PhD in CS, Statistics or related field
• Significant industry experience building ML pipelines and technical leadership
• Strong proficiency in Python and ML stack (PyTorch/TensorFlow)
• Proven experience deploying ML models to production
• Deep experience in content understanding (computer vision, NLP, multimodal/embedding models)

Responsibilities

• Lead modeling strategy for content understanding (vision, NLP, multimodal)
• Design and ship production models for content signals (embeddings, classifications)
• Own full ML lifecycle: data/labeling, training, evaluation, deployment, monitoring
• Partner with infra/platform teams for scalable training/serving
• Collaborate with signal-consuming teams (ranking, retrieval, integrity, ads) on signal contracts and metrics