Applied Scientist III - Recommendation Systems
Core
Design, build, and deploy large-scale recommendation systems and agentic AI workflows to power personalized lock screen and live entertainment experiences.
Role type
Senior IC Applied Scientist (Recommendation Systems & Agentic AI)
Builds
Production ML models, ranking algorithms, and autonomous agentic AI systems for consumer personalization
Domain
Consumer technology, mobile/TV commerce, agentic AI
Deliverable
production ML models
Required skills
Large-scale recommendation systems, classical ML, deep learning, NLP, reinforcement learning, statistical modeling, Python, big data processing (Spark), cloud computing
Preferred skills
LLMs, generative models, agentic/autonomous ML systems, retrieval systems, privacy-preserving ML
Technologies
PyTorch, TensorFlow, Spark, Hadoop, Azure, AWS, GCP, Vertex AI
Responsibilities
Design and develop large-scale recommendation systems using advanced ML and ranking algorithms; Build and operate machine learning models on high-volume data for personalization and prediction; Develop rapid experimentation workflows to validate hypotheses; Own data preparation, model training, evaluation, and deployment pipelines; Monitor ML model performance and identify drifts; Build and experiment with agentic AI systems that autonomously observe performance and tune hyperparameters; Apply LLMs and multimodal generative models for semantic understanding and user preference modeling; Collaborate with cross-functional teams to integrate ML features into consumer experiences.
Seniority
Senior, hands-on IC
