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.

• 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.

• 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.

• Work on the most important part of our system

• Work at a place that deeply cares about data quality

• 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.

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).