Doug Turnbull
Coaching Search Experts At Apple, Meta, OpenAI, AirBNB And More at SoftwareDoug LLC
Charlottesville, Virginia, United States
Summary
🤩
Rockstar🎓
Top SchoolDoug Turnbull is a search and ML-for-relevance specialist with 13 years of experience helping companies from Shopify and Reddit to Apple, Meta, OpenAI and Airbnb improve search quality and business outcomes. He led Learning-to-Rank efforts and large-scale relevance experimentation at Shopify and Reddit, built hybrid lexical+vector retrieval systems, and authored the influential Elasticsearch Learning to Rank plugin used by the community. Doug writes and teaches widely—authoring Relevant Search (2016) and AI Powered Search (2024) and running practical courses on agentic and ML-powered search—while consulting through SoftwareDoug LLC and coaching search teams at top tech firms. He combines hands-on engineering (feature extraction, model serialization, large-scale experimentation) with programmatic quality assessment like LLM-as-a-judge, and has a track record of turning search research into measurable product wins. Based in Charlottesville, VA, he enjoys mentoring the next generation of relevance engineers and shipping tools that make search both trustworthy and performant.
13 years of coding experience
3 years of employment as a software developer
Bachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at Virginia Tech
Stackoverflow
64,941reputation
10.0mreached
615answers
68questions
unix
top-5%
design-patterns
top-5%
queue
top-5%
dictionary
top-5%
elasticsearch
top-5%
oop
top-5%
Github Skills (50)
qt10
amazon-elasticsearch10
formatting10
query-optimization10
machine-learning10
volatile10
std10
feature-engineering10
elasticsearchquery10
stl10
php10
aws-elasticsearch10
increment10
elasticsearch10
elasticsearch-api10
Programming languages (9)
Github contributions (5)
o19s/elasticsearch-learning-to-rank
Dec 2016 - May 2020
Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch
Role in this project:
ML Engineer
ML EngineerContributions:378 commits, 90 PRs, 315 pushes in 3 years 5 months
Contributions summary:Doug's commits primarily focused on integrating Learning to Rank (LTR) models with Elasticsearch. They developed and tested a system for training LTR models using RankLib and integrating them as part of the Elasticsearch query process. The commits demonstrate the implementation of feature extraction, model serialization, and the incorporation of feature normalizations. The work included the creation of a full working example of using an LTR model to influence search results.
machine-learningelasticsearch-pluginelasticsearch-pluginslearning-to-rankrelevance
softwaredoug/subredis
Dec 2013 - Feb 2017
Yo Dawg I heard you liked Redis so I put more Redis in your Redis
Contributions:28 commits, 2 PRs, 4 pushes in 3 years 2 months
redisredis-clientredisearchdawgredis-search
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