Applied Scientist II
Core
Applying LLMs to improve search relevance and automate training data generation, building neural ranking models and feature processing frameworks.
Role type
Applied Scientist II (Search & Ranking)
Builds
Large-scale neural ranking models, feature processing frameworks, and scalable ML systems for search.
Domain
Search, Large Language Models, Reinforcement Learning
Deliverable
production ML models
Required skills
LLMs, transformer-based models, retrieval, ranking, neural network architectures, feature engineering, model optimization, Python, PyTorch, TensorFlow, distributed systems, data processing, system design
Preferred skills
reinforcement learning, online experimentation (A/B testing), user engagement optimization
Responsibilities
Apply LLMs to improve search relevance, automate training data generation, build state-of-the-art large-scale neural ranking models, develop scalable ML systems powering millions of daily search experiences.
Seniority
Mid-Senior, hands-on IC
