Principal Applied Scientist
Core
Lead advanced research initiatives in LLM post-training, alignment, and search capabilities (retrieval, ranking, RAG) to drive product opportunities and measurable business impact.
Role type
Principal Applied Scientist (LLM & Search Systems)
Builds
Next-generation search capabilities, LLM post-training/alignment methods, and RAG pipelines for production environments.
Domain
Artificial Intelligence, Large Language Models (LLM), Search, and Retrieval-Augmented Generation (RAG)
Deliverable
production ML models
Required skills
LLM post-training and alignment, retrieval and ranking system design, RAG pipeline architecture, hypothesis-driven experimentation, reproducible research methodologies, Python, C++, C#, C, Java, Machine Learning, NLP, large-scale ML system development
Preferred skills
Deep subject-matter expertise in statistics, predictive analytics, and applied research
Technologies
Python, C++, C#, C, Java
Responsibilities
Design, implement, and evaluate novel methods for LLM reasoning quality, safety, and factual grounding; build and optimize retrieval, ranking, and relevance systems; architect and refine RAG pipelines to reduce hallucinations; translate research into production via experiments and engineering collaboration; drive scientific rigor through documentation and hypothesis testing; collaborate across research, engineering, product, and design to shape long-term strategy; mentor team members and develop academic collaborators.
Seniority
Principal, strategy & mentorship
