Support Engineer

Reposted 4 Days Ago
San Francisco, CA
In-Office
120K-200K Annually
Mid level
Artificial Intelligence • Software
Building embeddings-based search infrastructure
The Role
The Support Engineer at Exa resolves engineering issues, assists customers, and manages support projects, contributing to AI search engine development.
Summary Generated by Built In

Exa is building a search engine from scratch to serve every AI application. We build massive-scale infrastructure to crawl the web, train state-of-the-art embedding models to index it, and develop super high performant vector databases in rust to search over it. We also own a $5m H200 GPU cluster and routinely run batchjobs with 10s of thousands of machines. This isn't your average startup :)

As a Support Engineer at Exa, you'll help to provide customer and internal team support by executing on engineering problems as they arise.

Desired Experience/Qualities

  • Several years of programming experience (Ex. could build a server in node.js)

  • Have experience responding to customer inquiries

  • Excited to diagnose and trouble shoot technical issues

  • Care about the problem of finding high quality knowledge and recognize how important this is for the world

Example Projects

  • Build an automated customer support bot from scratch

  • Create a support knowledge base for customer-facing information

  • Build an intelligent ticket routing system using machine learning to categorize and prioritize incoming support requests.

  • Fix bugs in the frontend or backend that customers point out

This is an in-person opportunity in San Francisco. We're happy to sponsor international candidates (e.g., STEM OPT, OPT, H1B, O1, E3).

Top Skills

Gpu Cluster
Machine Learning
Node.js
Rust
Am I A Good Fit?
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The Company
San Francisco, , California
86 Employees
Year Founded: 2021

What We Do

Exa was built with a simple goal — to organize all knowledge. After several years of heads-down research, we developed novel representation learning techniques and crawling infrastructure so that LLMs can intelligently find relevant information.

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