Senior Applied Scientist - Ads Ranking & Retrieval
Core
Advance R&D in retrieval, ranking, matching, and generative models for ads; train, fine-tune, align, and productionize SLMs/LLMs/LRMs to evolve the ads ranking platform.
Role type
Senior Applied Scientist (Ads Ranking & Retrieval)
Builds
Ads ranking platform, large-scale recommendation systems, production ML models
Domain
Online advertising, AI/ML, large-scale distributed systems
Deliverable
production ML models
Required skills
SLM/LLM/LRM training and fine-tuning, multi-stage ranking pipeline design, deep learning framework proficiency, distributed training on large datasets, training and inference optimization, platform architecture influence, cross-team roadmap alignment, tier-1 venue publication record
Preferred skills
None stated
Technologies
PyTorch, Hugging Face, TensorFlow
Responsibilities
Advance research and development across retrieval, ranking, matching, and generative models; Leverage and improve SLMs/LLMs/LRMs by training, fine-tuning, aligning, and productionizing models; Evolve the Ads ranking platform toward better usability, reliability, scalability, efficiency, and architectural coherence; Provide technical leadership on projects including setting direction, coaching a distributed team, and influencing cross-org strategy; Follow research trends in AI to guide the group in keeping solutions state-of-the-art; Collaborate with research and engineering teams
Seniority
Senior, hands-on IC with technical leadership
