Staff Software Engineer
Leads the development of machine-learning search relevance systems, including query understanding, ranking, retrieval, and evaluation at scale. Requires 10+ years of search relevance experience and expertise in ML, NLP, or related discovery technologies.
About the job
Responsibilities
- Drive the development and deployment of machine-learning-based search and discovery relevance models and systems integrated with Databricks products and services.
- Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewriting, ranking and retrieval, and model evaluation.
- Collaborate with product managers and cross-functional teams on technology initiatives for search and discovery experiences.
- Build a robust framework for evaluating search-ranking improvements through offline and online evaluation.
Requirements
- Bachelor's degree or higher in Computer Science or a related field; a master's degree or PhD is preferred.
- 10+ years of experience developing search relevance systems at scale in production or high-impact research environments.
- Experience applying large language models (LLMs) to search relevance.
- Experience in one or more of the following areas:
- Query understanding
- Natural language processing
- Text mining
- Recommendations
- Personalization
- Discovery
- Conversational AI
- Strong understanding of computer science fundamentals.
- Contributions to well-used open-source projects.
Benefits
- Comprehensive benefits and perks tailored to the needs of employees in each region.
Skills
Machine Learning, Natural Language Processing, LLMs, Search Ranking, Information Retrieval, Query Understanding, Text Mining, Recommendations, Personalization, Conversational AI, Model Evaluation, Open Source
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