Machine Learning Engineer
About Elicit
Elicit is the AI research assistant. We use language models to help researchers figure out what's true and make better decisions, starting with common research tasks like literature review.
What we're aiming for:
Elicit radically increases the amount of good reasoning in the world.
For experts, Elicit pushes the frontier forward.
For non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit.
Elicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes. This expands our collective understanding of safe AGI architectures.
Our Twitter page shows how Elicit helps researchers today. Our roadmap outlines our vision for how Elicit impacts more than research in the future.
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.)
You can review a longer list of the kinds of ML-related projects you'd be working on here.
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, however, 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.
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): $175-245K + equity
Senior (L4): $210-300K + equity
Expert (L5): >$275K + 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).
Join us!
About the job
Apply for this position
Machine Learning Engineer
About Elicit
Elicit is the AI research assistant. We use language models to help researchers figure out what's true and make better decisions, starting with common research tasks like literature review.
What we're aiming for:
Elicit radically increases the amount of good reasoning in the world.
For experts, Elicit pushes the frontier forward.
For non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit.
Elicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes. This expands our collective understanding of safe AGI architectures.
Our Twitter page shows how Elicit helps researchers today. Our roadmap outlines our vision for how Elicit impacts more than research in the future.
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.)
You can review a longer list of the kinds of ML-related projects you'd be working on here.
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, however, 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.
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): $175-245K + equity
Senior (L4): $210-300K + equity
Expert (L5): >$275K + 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).
Join us!