Senior Applied Scientist-Ads Relevance
Core
Defining ad relevance problems across scenarios to optimize user and advertiser experiences using deep learning, NLP, computer vision, and LLMs.
Role type
Senior Applied Scientist (Ads Relevance)
Builds
Robust, scalable ad relevance systems and agentic AI solutions for online advertising.
Domain
Online Advertising, Machine Learning, NLP, Computer Vision, LLMs
Deliverable
production ML models
Required skills
Deep learning (NLP, CV, LLMs), Transformer-based SLMs/LLMs, Python/C++, Distributed training/inference, Online advertising, Agentic AI systems, Responsible AI practices, Peer-reviewed conference publications
Preferred skills
Experience with task-specific offline metrics, human/model-assisted evaluation, safety/robustness testing, latency/cost analysis, controlled online experiments
Technologies
Python, C++, Vision Transformers, Large Language Models (LLMs), Small Language Models (SLMs), Mixed-precision training, Checkpointing, Experiment management
Responsibilities
Drive algorithmic and modeling improvements using deep learning; Deploy scalable solutions to improve ad relevance; Analyze model/system performance via offline/online testing; Design and implement agentic AI systems with tool calling, retrieval, and multi-agent coordination; Apply responsible AI practices for safety, bias, and privacy evaluation.
Seniority
Senior, hands-on IC
