Job Description
Role Overview:
Operate at the intersection of classical ML, large-scale recommendation systems, and agentic AI, building and deploying intelligent systems for personalized experiences and next-gen autonomous AI workflows.
Key Responsibilities:
- Design and develop large-scale recommendation systems using ML, statistical modeling, ranking algorithms, and deep learning.
- Build, operate, and monitor ML models on high-volume, diverse datasets for personalization, prediction, and content understanding.
- Develop rapid experimentation workflows to validate hypotheses and measure real-world impact.
- Build and experiment with agentic AI systems to autonomously improve workflows, tune hyperparameters, and optimize model performance.
- Apply LLMs, embeddings, RAG architectures, and multimodal generative models for semantic understanding and user preference modeling.
- Design intelligent agents to automate repetitive decision-making and feature selection.
- Collaborat...
Operate at the intersection of classical ML, large-scale recommendation systems, and agentic AI, building and deploying intelligent systems for personalized experiences and next-gen autonomous AI workflows.
Key Responsibilities:
- Design and develop large-scale recommendation systems using ML, statistical modeling, ranking algorithms, and deep learning.
- Build, operate, and monitor ML models on high-volume, diverse datasets for personalization, prediction, and content understanding.
- Develop rapid experimentation workflows to validate hypotheses and measure real-world impact.
- Build and experiment with agentic AI systems to autonomously improve workflows, tune hyperparameters, and optimize model performance.
- Apply LLMs, embeddings, RAG architectures, and multimodal generative models for semantic understanding and user preference modeling.
- Design intelligent agents to automate repetitive decision-making and feature selection.
- Collaborat...
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