
The data engineer’s solution to turning data into vector embeddings. Building LLM demos is cool, turning 1B user clicks and millions of documents into vectors is cooler.

The data engineer’s solution to turning data into vector embeddings. Building LLM demos is cool, turning 1B user clicks and millions of documents into vectors is cooler.
What they do: Build a Python framework and managed product that converts semi-structured and multi-modal data into vector embeddings for search, RAG, recommendations, and analytics.
Headquarters: San Francisco, California
Founders: Daniel Svonava and Ben Gutkovich
Recent funding: $9.5M Seed announced Mar 2024 (lead: Index Ventures)
Employees: 36
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Vector search and matching for semi-structured and multi-modal data; productionizing embeddings at scale.
2021
Data Infrastructure and Analytics
$9.5M
Seed round announced March 2024.
“Index Ventures led the Seed; participating investors reported include MMC Ventures and individual angels.”
The role & what you’ll do
Help build the next generation of AI Search at an Index Ventures-backed Silicon Valley startup based in Budapest, using cutting-edge AI tools.
This role is only available for contractors based in Hungary.
Tech stack
Soft skills
Performance-driven
Understands how to leverage AI tools to achieve exceptional engineering speed and quality. Continuously seeks opportunities to enhance productivity through expert use of modern technologies.
Pragmatism
Delivers the simplest, most effective solution that provides value today. Prioritizes clarity and simplicity over unnecessary complexity or elegance.
Ownership
Consistently considers the broader business and product impact. Proactively identifies and solves critical problems even in ambiguous or rapidly evolving environments.
Organized work style
Maintains a structured and methodical approach, whether collaborating with a team or working independently. Practices include small iterative development, clear branching strategies, and thoughtful documentation.
About Superlinked
Superlinked is creating models and infrastructure that connect structured and unstructured data to power the next generation of search, matching, and recommendation systems.
Our technology is already at work for industry leaders in e-commerce, media, and manufacturing, processing terabytes of data and millions of queries every day to deliver faster, smarter, and more relevant results.
With $12M+ in top-tier funding and a team of ex-Google and AWS engineers, we’re scaling fast through partnerships that bring our technology to more developers.