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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
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 .)
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.
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Oakland, USA
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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
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.)
You can review a longer list of the kinds of ML-related projects you'd be working on here.
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.
AI research assistant for automated literature review and analysis.
Visit company websiteJobs and hiring trendsUSD 185000-340000 yearly / year
Full-time
Senior
Hybrid
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