AI Embeddings Engineer

Help companies turn their documents and data into embeddings that retrieval and search systems can rely on.
Through Nebulai's marketplace, you join teams running LLM and search systems in production. You choose and evaluate embedding models, build the pipelines that chunk, embed, and index content, and track down the drift and quality issues that quietly hurt retrieval results.
You'll be a strong fit if you:
- Have built and run embedding and indexing pipelines for production retrieval or search
- Have compared embedding models using real evaluation sets, not leaderboard numbers
- Know how to handle re-embedding, index versioning, and drift as data and models change
- Can explain retrieval quality tradeoffs to product and engineering teams
Bonus if you've worked in regulated industries, or across on-prem and multi-cloud stacks without favoring a vendor.
Contract AI embeddings work via Nebulai. Apply at https://nebulai.app

Work arrangement
Yes