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tensorflow pytorch data pipelines llms production systems📋 Description
- Build and scale machine learning systems that generate deep understanding of content across modalities
- Develop models for classification, tagging, semantic understanding, and content enrichment
- Create high quality content enrichment at scale using LLMs and agentic systems.
- Design systems that make content intelligence signals available to downstream teams and products
- Improve automation for content quality, safety, and metadata enrichment at scale
- Collaborate with product, policy, and engineering teams to translate content intelligence into user impact
- Contribute to evaluation frameworks, data pipelines, and annotation systems
- Support rapid experimentation to prototype and launch new types of content signals
- Help improve system reliability, scalability, and performance across large datasets
🎯 Requirements
- You have experience building and deploying machine learning systems in production
- You are comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar
- You have experience working with large datasets and care about data quality and evaluation
- You are interested in or have worked with multimodal machine learning
- You understand how to design systems that balance automation with quality and user experience
- You are comfortable working on complex problems with evolving requirements
- You think in systems and understand how models connect to product outcomes
- You communicate clearly and work well across technical and non-technical teams
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