About the Role

The Search team at the New York Times is responsible not just for helping our readers find the journalism they're looking for—we're transforming search into an experience that helps them explore the full range of what we have to offer. You'll collaborate with a team that includes product, design, data, and editorial partners to harness advancements in AI and help transform our millions of queries each day into opportunities for discovery. You will report to the Engineering Manager of Search & Personalization.

Responsibilities:

Lead the development and optimization of semantic search algorithms and systems using technologies such as Elastic/OpenSearch/Solr. Apply machine learning techniques, including classification and ranking models, to fine-tune search relevance. Draw on your experience with Kubernetes and Kafka to build scalable and resilient search infrastructure. Contribute to the exploration and integration of Retrieval-Augmented Generation and Large Language Models into search experiences. Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

5+ years of relevant experience in search engineering, information retrieval, or related field. 3+ years experience with Elastic, OpenSearch, Vespa, Solr or any other open source search engines. 3+ years of experience programming backend applications using Java, Go, or Clojure.

Preferred Qualifications:

Experience with Kafka/PubSub for building distributed systems and event-based architectures. Experience with Kubernetes for deploying and managing search infrastructure.

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-018816