ML Research Resident
Posted 689 days ago, which is unusual. The employer's own board was still carrying it when we last read it, 5 hours ago.
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 689d ago
The date the source published, not the day we noticed it (2024-12-13). Last seen at its source 5h ago.
We have tracked this listing since 3 Sep 2026 (59 days). The employer's own board has carried it every time we have read it, most recently 5 hours ago.
Is it remote?
Oakland, CA (or remote within US timezones)
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description agrees: it names United States.
What the ad says
…Location: In-person (Oakland) or remote (US) Potential of full-time of…
Pay not stated
Similar roles pay $105k–187.2k/yr
Middle 50% of 1731 listings that do state pay — Operations · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Carried by 1 source
-
Ashby employer's own board first seen 59d ago · last seen 5h ago
The listing
Elicit is building a research agent that can use an unlimited amount of test-time compute while keeping its reasoning transparent and verifiable.
The residency
Transformers do a fixed amount of computation per token, and the quality of work degrades rapidly when they are applied iteratively. As research resident, you'll work with us for 3 months on developing computational procedures (operators) that can reliably improve a knowledge state over thousands of iterations.
What is a knowledge state? A knowledge state consists of structured information - for example, a scientific paper might be represented as a set of claims supported by evidence and connected through logical reasoning; this might be combined with scratchpads, evergreen “notes to self”, search trees, and other information.
What counts as improvement? Like scientists, we want LLMs to make genuine progress in understanding - separating inferences from raw evidence, finding connections between ideas, building clearer explanations, and identifying gaps in reasoning. But unlike typical ML systems that are often trained to do “whatever works”, we need improvements that are epistemically sound - each step should make the knowledge state more useful while remaining human-readable. An improvement might reorganize information to better answer a question, find an implicit assumption in an argument, or connect evidence across multiple sources.
As research resident, your work will focus on designing and testing improvement operators that maintain stability over 1000+ iterations while making genuine progress. You'll start with simple cases (e.g., shallow refactoring of scientific papers) and demonstrate reliable iteration before scaling to more complex reasoning tasks.
Developing systems that perform legible reasoning over long horizons addresses core challenges in AI transparency and scalable reasoning.
About you
Strong candidates will have experience with LLMs, good intuitions about what makes reasoning systematic and verifiable, and care about AI transparency.
The best applicants will additionally have a strong software engineering background and concrete examples of how they've applied this background to come up with novel abstractions that push the frontiers of automated reasoning.
Logistics
3-month contract role
Compensation: $12-15k/month depending on experience
Location: In-person (Oakland) or remote (US)
Potential of full-time offer for exceptional candidates
Location and travel
We have a great office in Oakland, CA, and we'd love to see you there if you're local. That said, we're just as happy for you to work remotely. We do get the whole team together for a quarterly retreat somewhere fun, because in-person time matters to us.