AI Search and Match Engineer

Required Skills Strong experience with Apache Solr or Elastic Search (schema design, edismax, fq/bq tuning) Solid understanding of vector databases preferably Milvus, or alternatives like Pinecone, Weaviate, FAISS Hands-on experience with embedding models (e.g., OpenAI embeddings, BERT variants) Experience with normalization/ontology systems for skills and titles Familiarity with information retrieval techniques, relevance tuning, and scoring strategies Comfortable working with structured/unstructured data from resumes and job descriptions Understanding of search evaluation metrics Familiar with NLP libraries: spaCy, Hugging Face Transformers, or similar Nice-to-Have Skills Experience with Neo4j for knowledge graphs Experience with ML model deployment or ranking models Experience in building search analytics dashboards Familiarity with Redis, MySQL, or Elasticsearch a plus Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.