Machine Learning Engineer

Elicit, Oakland, CA (or remote within US timezones)

The role

As a Machine Learning Engineer at Elicit, you’ll build products and workflows that help researchers and scientific teams make higher quality decisions with language models.

This is not a role for someone who only wants to develop models in isolation from user impact. A large part of the work is software engineering: building product experiences, APIs, data integrations, evaluation systems, and reliable harnesses that make language models reliably useful and trustworthy in high-stakes domains.

What you will do

You’ll work on problems like

Turning messy, ambiguous research tasks into clear product experiences
Building interfaces and artifacts that help users understand, trust, and act on model outputs, thinking beyond the chat interface while leveraging full model capabilities
Combining language models with external tools, structured and unstructured data, and retrieval systems
Improving quality through building careful evaluations, truth-conducive model environments and tools, and targeted ML modeling where the impact is high

All jobs

Machine Learning Engineer

Elicit, Oakland, CA (or remote within US timezones)

The role

As a Machine Learning Engineer at Elicit, you’ll build products and workflows that help researchers and scientific teams make higher quality decisions with language models.

What you will do

You’ll work on problems like

Turning messy, ambiguous research tasks into clear product experiences
Building interfaces and artifacts that help users understand, trust, and act on model outputs, thinking beyond the chat interface while leveraging full model capabilities
Combining language models with external tools, structured and unstructured data, and retrieval systems
Improving quality through building careful evaluations, truth-conducive model environments and tools, and targeted ML modeling where the impact is high

What you need

What you bring

A strong software engineering background and can build end-to-end systems, not just scripts or notebooks
Fluency with language models to reason well about prompting, retrieval, evals, failure modes, and where (and how) finetuning is or isn’t worth it
Strong product sense and likes turning fuzzy user problems into concrete things people can use
An excitement to solve difficult, creative problems rather than narrow optimization on well-defined benchmarks
Ability to move across backend, data, and model layers as needed
Clear communication with product, design, domain experts, and other engineers
Ability to use coding assistants effectively and thoughtfully, and has adapted their workflow to become much more effective with them

To get a sense for how some of us look at applications, see this thread https://twitter.com/stuhlmueller/status/1704543826218729868. (The short version: Wherever we can, we prefer to directly evaluate work.)

You’ll thrive here if you

Like shipping user-facing things quickly
Enjoy working on ambiguous problems with a lot of autonomy
Care about product quality and user trust, not just technical novelty
Want to build new kinds of software made possible by language models
Are excited to use AI tools as part of your daily engineering workflow, while still applying strong judgment

What we’re not looking for

This is probably not the right role if you mainly want to

do low-level model systems work like CUDA optimization or model serving infrastructure as your primary focus
work only on research experiments without owning production systems
optimize benchmark numbers without much connection to user workflows or product outcomes

We do care about model quality, evals, and sometimes finetuning. But those matter because they help us build products users can rely on, not as ends in themselves.

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?

[https://app.ashbyhq.com/api/images/user-content/797554ae-ec94-4cd4-8a92-0ca2488582e0/b3dfeb51-0b0a-456d-bab1-5e1fd385abab/elicit-team-2.jpeg]

Pay and benefits

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 https://www.notion.so/elicit-research/In-person-work-at-Elicit-How-we-combine-remote-flexibility-with-in-person-time-233cfae9876c80f8802ed08d4c2548a5?source=copy_link
Fully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your family
Flexible vacation policy, with a recommendation of 20 days/year + company holidays
401K with a 6% employer match
Every Elician receives a $200 monthly wellbeing stipend to spend on whatever supports your health and wellbeing.
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 https://twitter.com/stuhlmueller/status/1694059800408269091.

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): $185-220K + equity
Senior (L4): $220-260K + equity
Expert/Staff (L5): $250-320K + 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.

JOIN US!

Machine Learning Engineer

The role

What you will do

You’ll work on problems like

Machine Learning Engineer

The role

What you will do

You’ll work on problems like

What you’ll build

What you need

What you bring

You’ll thrive here if you

What we’re not looking for

This is probably not the right role if you mainly want to

Consider these questions

Examples of projects you could work on

Location and travel

Pay and benefits

Benefits

Compensation

About Elicit

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