Job Description

Elicit is building the reasoning layer for science and decision-making. We use language models to search over 125 million papers, extract data, and surface insights so that researchers, policy-makers, and industry leaders can go from questions to evidence-backed decisions in minutes.

Today, hundreds of thousands of researchers have used Elicit to speed up literature reviews, automate systematic reviews, and explore new domains. As we expand our impact beyond academic research, we are laying the groundwork for ML systems that are  systematic, transparent, and unbounded when reasoning at scale.

To do this, Elicit is pioneering  supervision of process, not outcomes . Instead of favoring large black-box models, we break complex questions down into human-legible steps and supervise the reasoning process itself. This approach delivers more transparent, defensible answers today and charts a safer path toward advanced AI tomorrow.

Our vision is ambitious: we’re building the default starting point for understanding and reasoning through any hard question. We invite you to help us build that future.

(See how people use Elicit today on  Twitter ; explore our vision in the  roadmap .)

About the role

As an ML research engineer at Elicit, you will: 

• Compose together tens to thousands of calls to language models to accomplish tasks that we can't accomplish with a single call.

• Curate datasets for finetuning models, e.g. for training models to extract policy conclusions from papers

• Set up evaluation metrics that tell us what changes to our models or training setup are improvements

• Scale up semantic search from a few thousand documents to 100k+ documents

About you

To help us get there:

• You need to have a strong software engineering background. We want to apply your experience building systems, designing architecture, and thinking about good abstractions. Elicit will need you to do much more than write scripts.

• You must be familiar with language models (training, fine-tuning, evaluation), or have a comparable machine learning or natural language processing background (e.g. experience with information extraction, semantic search)

• You'll need a startup mindset. We expect to measure our impact in part by the people whose lives we improve through reasoning and models of the future. We know you care about that too. You’ll want to test lots of ideas, get feedback, and watch yourself learning and growing every day.

To get a sense for how some of us look at applications, see  this thread . (The short version: Wherever we can we prefer to directly evaluate work.)

Location and travel

We have a lovely office in Oakland, CA, but we don't all work from there all the time. It's important to us to spend time with our teammates, so we ask that all Elicians spend 1 week out of every 6 with teammates.

• We have a quarterly team retreat,  normally in and around the SF bay area.

• We have quarterly co-working weeks (offset from the team retreats) in our Oakland office.

• If you come to the retreats and co-working weeks, you'll meet our expectations for in-person time!

• There is flexibility around the specifics here : if you're not sure you can make this work, get in touch.

Am I a good fit?

Consider these questions:

• How does a transformer work?

• What is a tokenizer?

• What is a decorator in Python?

• What are generic types?

Strong applicants will find it easy to answer these questions.

Benefits

In addition to working on important problems as part of a happy, productive, and positive team, we also offer great benefits (with some variation based on work location):

• Flexible work environment - work from our office in Oakland or remotely  as long as you can travel to work in-person for retreats and coworking events

• Fully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your family

• Flexible vacation policy, with a minimum recommendation of 20 days/year + company holidays

• 401K with a 6% employer match

• A new Mac + $1,000 budget to set up your workstation or home office in your first year, then $500 every year thereafter

• $1,000 quarterly AI Experimentation & Learning budget, so you can freely experiment with new AI tools to incorporate into your workflow, take courses, purchase educational resources, or attend AI-focused conferences and events

• A team administrative assistant that you can delegate personal and work tasks to

• Commuter benefits, a relocation bonus, and more!

• You can find more reasons to work with us  in this thread .

Compensation

For all roles at Elicit, we use a data-backed compensation framework to make sure our salaries are market-competitive, equitable, and simple. For this role, we're targeting starting ranges of:

• Career (L3): $185-250K + equity

• Senior (L4): $230-300K + equity

• Expert/Staff (L5): $255-340K + significant equity

We're optimizing for a hire who can contribute at a L4/senior-level or above. We'd love to meet staff/principal level contributors as well.

We also offer above-market equity for all roles at Elicit, as well as employee-friendly equity terms (10-year exercise periods).

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