THE PURPOSE:

We are building a new search, discovery, and shopping graph platform that powers the suite of Slickdeals product lines. We’re looking for top-notch search engineering talents in the area of information retrieval, search indexing, Elasticsearch, Lucene, algorithms, relevance & ranking, data mining, machine learning, data analysis & metrics, query processing, multi-lingual search and multi-modal search.

In this role, you will be part of our unique Search and Discovery team. We are looking for someone with expertise in information retrieval and a passion for creating exceptional search experiences. The ideal candidate will have a strong technical background and a deep understanding of search algorithms and systems. As an individual contributor to the Search and Discovery Team, you will play a crucial role in enhancing our search capabilities and driving the discovery of deals and content for our users. You will be building products using technologies such as AWS SageMaker,  Tensforflow, Pytorch, LLM, Elastic Search, REST web services, SQS/Kafka, Vector Database, HBase, Machine Learning, and more.

THE ROLE:

• Working with data scientists and engineers to productionize cutting-edge data products via
  load testing, metrics analysis, and offline and online experimentation, so they can scale to
  support millions of buyers around the world.
• Designing and implementing features to improve the relevance of search and
  recommendation experiences, including semantic search, query understanding, and
  personalization.
• Building and maintaining data pipelines to power our information retrieval systems.
• Tuning the ElasticSearch (or similar search technology) queries that power our search and
  discovery experiences.
• Prioritizing and communicating to technical and non-technical audiences alike
• Mentoring engineers and data scientists

QUALIFICATIONS:

• 5+ years total professional experience as a software engineer
• Substantial development and administration experience in search technology (Elasticsearch,
  Opensearch, Apache Solr, and/or Algolia)
• Experience in performance tuning, query analysis, defining success criteria and metrics,
  designing ranking and relevance experiments and optimizing Elasticsearch
• Knowledge of high availability and disaster recovery options for search
• Observed and identified service pain points, priorities, requirements, and success criteria
  Exposure to a variety of data stores and search technologies (e.g. MySQL, RDS, MongoDB,
  DynamoDB, Redis, Open Search, Elasticsearch, Neo4j)
• Familiarity with AWS, GCP and/or other cloud computing platforms
• Prior experience with Python, SQL, and/or GraphQL
• Understanding of best practices in database design, data architecture, and performance
  tuning
• First-hand experience in building, scaling, and supporting large-scale data infrastructure
  systems in production
• Hands-on experience in building machine learning-based search and recommendation
  systems
• Experience with implementing ML-based search systems such as query classification,
  learning to rank or machine-learned ranking (MLR) search is a plus