Research, Exa

Evals

$150-300k

+ Offers Equity

Python

Rust

Mid and Senior level

San Francisco Bay Area

More information about location

Search infrastructure for AI

Be an early applicant

Search infrastructure for AI

21-100 employees

B2CB2BArtificial Intelligence

Be an early applicant

$150-300k

+ Offers Equity

Python

Rust

Mid and Senior level

San Francisco Bay Area

More information about location

21-100 employees

B2CB2BArtificial Intelligence

Company mission

To understand any query – no matter how complex – and filter the internet to exactly the knowledge required for that query.

Job

Company

Role

Who you are

Have hands-on ML experience (training, finetuning, or evaluating models (bonus if related to embeddings or LLMs)
Have strong engineering fundamentals and can build reliable systems (Python, Rust, distributed pipelines, GPU/cluster jobs, etc.)
Enjoy diving into data via building eval sets, inspecting edge cases, designing creative measurement strategies

What the job involves

We're looking for an ML evals engineer to design and build our eval stack at Exa
The role involves investigating how to evaluate search engines in an LLM world and then building the most comprehensive, creative, and effective eval suite
You will be deciding the future of search through the evals we choose to optimize for
Write a manifesto of what perfect search means
Design and implement evaluation frameworks that probe the limits of search
Build scalable, reliable eval pipelines that track regressions, drift, and quality signals across billions of documents
Create golden datasets, synthetic benchmarks, agentic tasks, and real-world test suites that reflect how developers, agents, and humans actually use Exa
Partner closely with ML researchers, data engineers, infra engineers, and product to shape the feedback loops that improve our search models

Our take

The way we currently query AIs means that the models we rely on are themselves reliant on the quality of internet search tools. To answer this, Exa is building a tool that allows AI models to perform the equivalent of a web search, making the models more effective in their responses to our questions.

Exa’s embeddings-based search engine is free of “hallucinations” (those bizarre search query answers that AI sometimes brings back to users). Also, in the same way that LLMs complete sentences, its predictive technology does the same for search queries by providing the next probable link.

It's an alluring product for companies and individuals who want to accelerate their research answers. It's also one of a kind at present, which has led to several successful funding rounds which will help accelerate its product. If it maintains its current momentum, Exa could well be the AI search engine of the future.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 5 rounds)

Sep 2025

$85m

SERIES B

Jul 2024

$17.6m

SERIES A

Total funding: $112.2m

Company HQ

Lower Haight, San Francisco, CA

Leadership

Will Bryk

(Co-Founder & CEO)

Previously a Software Engineer at Cresta, Intern at Zoox Inc and was the President of the Harvard Undergrad Robotics Club.

Jeffrey Wang

(Co-Founder)

Previously a Member of South Park Commons and was a Software Engineer at Plaid.

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