Head of Data Engineering

Sorry, this job was removed at 08:51 p.m. (CST) on Friday, Jun 07, 2024
San Francisco, CA
Hybrid
7+ Years Experience
Artificial Intelligence • Machine Learning • Other
The Role

Summary

We believe that high quality data is the most important part of creating high performance machine learning systems, regardless of whether they are simple classifiers or state of the art reasoning agents. We view this work as one of the most important at the company, and want someone who is solely dedicated to coordinating our efforts across the diverse range of data that matters to us.


In this role, you will lead our data engineering efforts. You will coordinate everything from human data collection processes to the collection, filtering, and preprocessing of raw web data, longer texts, code, and other generated data. You will be responsible for the ultimate quality and quantity of data on which we can train our systems, which is the primary factor in their performance. You will both direct this work, and get into the details yourself to ensure that we are constantly improving our data quality.


Example projects

Scan one million physical books and convert them into high quality pretraining data.

Find 90% of the most useful text available online and make clean training data from it.

Generate pretraining data in ways that are guaranteed to have low error.

Measure and understand the quality of each of our datasets.

Ensure that researchers and engineers can quickly and easily acquire human labels for a dataset.



You are

Passionate about data. You should be happy to look at and deeply engage with the raw data.

An excellent software engineer. We care about engineering best practices.

A great communicator. You will need to coordinate efforts between multiple external organizations and within our own team.

Familiar with python.



Compensation and Benefits

Work on the most important part of our system

Work directly on creating software with human-like intelligence.

Generous compensation, equity, and benefits.

$20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

Actively co-create and participate in a positive, intentional team culture.

Spend time learning, reading papers, and deeply understanding prior work.

Frequent team events, dinners, off-sites, and hanging out.

Work at a place that deeply cares about data quality.

Compensation packages are highly variable based on a variety of factors. If your salary requirements fall outside of the stated range, we still encourage you to apply. The range for this role is $200,000–$450,000 cash, $500,000–$4,000,000 in equity.



How to apply


All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.


We try to reply either way within a week or two at most (usually much sooner).


Learn more about our full interview process here.



About us


Imbue builds AI systems that reason and code, enabling AI agents to accomplish larger goals and safely work in the real world. We train our own foundation models optimized for reasoning and prototype agents on top of these models. By using these agents extensively, we gain insights into improving both the capabilities of the underlying models and the interaction design for agents.


We aim to rekindle the dream of the *personal* computer, where computers become truly intelligent tools that empower us, giving us freedom, dignity, and agency to pursue the things we love.


The Company
HQ: San Francisco, CA
15 Employees
Hybrid Workplace
Year Founded: 2021

What We Do

We build AI systems that can reason, in order to enable AI agents that can accomplish larger goals and safely work for us in the real world. To do this, we train foundation models optimized for reasoning. On top of our models, we prototype agents to accelerate our own work, seriously using them in order to shed light on how to improve the underlying model capabilities, as well as the interaction design for agents.

We aim to rekindle the dream of the *personal* computer—for computers to be truly intelligent tools that empower us, giving us freedom, dignity, and agency to do the things we love.

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