Data annotator

Job Title:

In this role, you’ll tackle new challenges in large language models (LLMs) and generative AI as part of a world-class team of research scientists and machine learning engineers.

You’ll conduct research that can be applied across engineering teams, engage in external collaborations and mentoring, and contribute to work in areas such as LLM training and adaptation, instruction tuning and alignment, retrieval-augmented generation (RAG), multimodal foundation models, personalization and user modeling with LLMs, LLM evaluation and benchmarking, efficient training and inference, safety alignment, and inclusive AI.

What you’ll do:

Contribute to cutting-edge research in LLMs and generative AI that can be applied to real-world product and engineering challenges
Collect, analyze, and synthesize data to translate research insights into practical, scalable solutions
Curate and generate high-quality training data with strong quality controls
Build reliable evaluation strategies for LLM systems, including offline metrics, human evaluation, red-teaming, robustness, and safety
Write clean, efficient, and maintainable code, and collaborate closely with engineering partners to deploy research into production systems
Develop LLM-powered methods to solve modeling and ranking problems across areas such as growth, discovery, advertising, and search