# Research, Evals at Exa

> Onsite · United States · Unspecified · Other · open. Source: https://alderhq.app/jobs/ashby%3Aexa%3A9c45a74e-d507-482a-bc0e-da2f464c9767 (read 2026-11-06).

## Facts (observed)

- Company: [Exa](https://alderhq.app/companies/exa)
- Location text: San Francisco, California
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco, California")
- Posted: 2025-10-15 (387 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/exa/9c45a74e-d507-482a-bc0e-da2f464c9767
- Skills listed (inferred): Python, Rust, LLMs

## Pay and sponsorship

- Posted pay: $180k–$350k per year (from the listing's pay field)
- Market band for similar posted roles (SF Bay Area, n 2393): p25 $100k, median $156k, p75 $210k

## Description (the employer's text)

Exa is an applied AI lab building a search engine unlike the world has ever seen. We build massive-scale infra to crawl the entire web, train state-of-the-art embedding models to process it, and design super high performant vector databases to retrieve over it. We now power search for Cursor, Cognition, HubSpot, and over 400,000 developers and have raised $350m from Lightspeed, Benchmark, and a16z.

Our ultimate goal is to build perfect search over all the world's information, far beyond Google. If you want to build massive-scale ML systems that will define the way the new AI world consumes information, this is the place for you.

### Research at Exa

The ML organization sits at the heart of our mission. We train foundational models for search. Our goal is to build systems that can instantly filter the world's knowledge to exactly what you want, no matter how complex your query. Basically, put the web into an extremely powerful database.

And to do that well, we need to measure what “good search” actually means. That’s where you come in.

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 - your work will directly influence what the research team works on and shape the direction of the company.

### 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 You Could Do

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

### Logistics

Location: This is an in-person opportunity in San Francisco.

Visas: We're happy to sponsor international candidates (e.g., STEM OPT, OPT, H1B, O1, E3). While we cannot guarantee your visa, we have historically been successful in sponsoring candidates from all over the world. If you receive an offer, our team will work hard to get you a visa.

Benefits: We offer premium healthcare benefits (medical, dental, vision), fertility benefits, 16 weeks of fully paid parental leave for all new parents, and a monthly wellness stipend to all of our employees.

Exa is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, marital status, pregnancy or related conditions, criminal histories consistent with applicable law, or any other basis protected by applicable law.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Aexa%3A9c45a74e-d507-482a-bc0e-da2f464c9767 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.