Staff Applied Scientist - I
Core
Design, build, and deploy intelligent systems powering personalized lock screens and live entertainment experiences at the intersection of classical ML, large-scale recommendation systems, and agentic AI.
Role type
Staff Applied Scientist (ML & Agentic Systems)
Builds
Personalized discovery interfaces, autonomous ML workflows, and ranking policies for consumer technology platforms.
Domain
E-commerce, Consumer Technology, AI/ML
Deliverable
production ML models
Required skills
Large-scale recommendation systems, Classical ML, Deep Learning, Agentic AI systems, LLMs, Reinforcement Learning, Big data processing, Cloud computing, Python, Statistical modeling
Preferred skills
Generative models, Retrieval-augmented architectures, Privacy-preserving ML, Identity-less ecosystems
Technologies
PyTorch, TensorFlow, Spark, Hadoop, Azure, AWS, GCP, Vertex AI, LLMs, Embeddings
Responsibilities
Design and develop large-scale recommendation systems using advanced ML and ranking algorithms; Build and operate machine learning models on diverse, high-volume data sources; Develop rapid experimentation workflows to validate hypotheses; Own data preparation, model training, evaluation, and deployment pipelines; Monitor ML model performance using statistical techniques; Build and experiment with agentic AI systems that autonomously observe model performance and tune hyperparameters.
Seniority
Staff, hands-on IC with strategic impact
