Staff Software Engineer - Machine Learning
Leads the development of machine-learning search relevance systems, including query understanding, ranking, retrieval, and evaluation pipelines. The role requires 10+ years of search relevance experience and expertise in NLP, LLMs, or related discovery technologies.
About the job
Key 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 machine learning and natural language processing pipelines for data preprocessing, query understanding and rewriting, ranking and retrieval, and model evaluation.
- Enable rapid experimentation and iteration across search and discovery systems.
- Collaborate with product managers and cross-functional teams on technology initiatives and product roadmaps for the search and discovery experience.
- Build a robust framework for evaluating search-ranking improvements, both offline and online.
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 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.
Compensation and Benefits
- Comprehensive benefits and perks are offered, with specific details varying by region.
Skills
Machine Learning, Natural Language Processing, LLMs, Search Relevance, Query Understanding, Text Mining, Information Retrieval, Recommendations, Personalization, Conversational AI, Ranking Models, Model Evaluation, Open Source
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