Research
Conducts machine learning research for web search by designing transformer architectures, training embedding models, building large-scale datasets, and developing evaluation systems. Requires graduate-level ML experience or exceptional undergraduate ability and strong PyTorch skills.
About the job
Responsibilities
- Train embedding models for search over the web.
- Develop novel transformer-based search architectures.
- Create large-scale datasets and analyze data deeply.
- Build evaluation systems to measure search quality and model progress.
- Pre-train models at very large scale, including models with hundreds of billions of parameters.
- Build RLAIF pipelines for search.
- Implement novel architectures and improve model performance against internal state-of-the-art results.
Requirements
- Graduate-level machine learning experience, or exceptional undergraduate experience.
- Ability to implement a transformer from scratch in PyTorch.
- Interest in creating large-scale datasets and conducting deep data analysis.
- Strong interest in finding and evaluating high-quality knowledge.
Compensation and Benefits
- Premium medical, dental, and vision healthcare benefits.
- Fertility benefits.
- 16 weeks of fully paid parental leave for all new parents.
- Monthly wellness stipend.
Skills
Machine Learning, Transformers, PyTorch, Embedding Models, Search Architectures, Large-Scale Datasets, Rlaif, Model Pre-Training, Model Fine-Tuning, Evaluation Systems
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