Lustre provides incredibly reliable product recommendations to help people choose what to buy. One of the most critical components in our system is the knowledge graph that processes our scraped data and transforms it into highly structured and contextualized input to our neural net.
You'll be an engineer on the knowledge graph. Some examples of the type of tasks you'll be doing:
- Automatically process massive amounts of structured data.
- Understand the context of the information to create useful connections to aid in predicting the best products.
- Research and implement new traversals of our knowledge graph to gain more leverage from our data.
- Figure out efficient ways to incorporate human-in-the-loop curation for tasks that cannot be automated.
- Communicate with the machine learning team to get them the data they need for improving recommendations.
- Keep an eye out for new technologies and data sources that can automate tasks or improve the quality of our data.
- Implement API routes for serving knowledge graph data to the frontend.
- Write and maintain thorough unit and integration tests.
An ideal candidate will:
- Be a capable problem solver who enjoys identifying business problems you can solve with thoughtful engineering
- Have 4+ years experience building out backend services (bonus points for ops knowledge).
- Enjoy digging through data to solve problems and find new optimizations.
- Have strong communication skills - this role will work with both the product & ML teams to understand their problems/goals.
We help people make the right decision on what to buy. To do this we indexed the world's product knowledge and then taught a neural net to replicate the research process of a savvy shopper.
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