Tasks:
- * Architect end-to-end search and retrieval pipelines
- * Build scalable production ML systems
- * Deploy and monitor production ML models
- * Design and optimize search relevance and ranking
- * Develop query understanding capabilities
- * Mentor engineers and collaborate cross-functionally
- * Optimize search latency and scalability
Perks/Benefits:
Skills/Tech stack required:
[English] [Faiss] [Information Retrieval] [Intent Classification] [Java] [Learning systems] [Machine Learning] [Machine learning systems] [Mandarin] [Model Deployment] [Model Monitoring] [Query rewriting] [Query Understanding] [Recommendation Systems] [Search & Ranking] [Search Relevance] [Search Systems] [Semantic Parsing] [Vector Search]
Educational requirements:
N/A
Role(s):
[AI Engineer] [Engineer] [Learning Engineer] [Machine Learning Engineer] [Search Engineer]