Data Engineer - Multimodal Systems

As a Data Engineer - Multimodal Systems, you will be a core contributor to creating, collecting, and improving Zyphra's datasets and data pipelines across a variety of modalities. Your work will intersect with almost every team at Zyphra. You will be involved in collecting large-scale datasets and implementing and optimizing highly parallel data pipelines.

Large-scale data collection across a variety of modalities (text, audio, image)

Designing and working with highly efficient, parallelized data processing pipelines across modalities

Designing and running rigorous experimental ablations to demonstrate the impact of new data improvements

Our research methodology is grounded in methodical, step-by-step approaches to ambitious goals. Both deep research and engineering excellence are equally valued

We strongly value new and crazy ideas and are very willing to bet big on new ideas

We move as quickly as we can; we aim to minimize the bar to impact as low as possible

We all enjoy what we do and love discussing AI

Strong implementation and prototyping ability

Can take an idea from conception to experimentation quickly

The ability to work well with others in a high-paced research setting

Can rapidly learn new fields and are excited to implement new ideas

Excellent communication and collaboration skills, and can work effectively on both research and engineering implementation at scale.

Experience collecting, handling, and processing large datasets

Experience with parallel Python programming frameworks such as Dask

Understanding of the state-of-the-art in dataset curation across modalities

A generally meticulous nature and a strong interest in actually looking at data and sanity checking things

Strong grasp of proper experimental methodology for running rigorous ablations and other hypothesis testing

Understanding of and interest in large-scale, highly parallel data processing pipelines.

Proficiency with PyTorch and Python.

Experience contributing to large pre-existing codebases and rapidly getting up to speed.

Previously published machine learning research in well-respected venues.

Postgraduate degree in a scientific subject (Computer Science, EE/EECS, Mathematics, Physics, Machine Learning)