Zyphra
Data Engineer - Multimodal Systems
3mo ago
USApythondask
Responsible for creating, collecting, and improving large-scale multimodal datasets and data pipelines.
Responsibilities
- 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.
Requirements
- 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)
Conditions
- Comprehensive medical, dental, vision, and FSA plans
- Competitive compensation and 401(k) plan
- Relocation and immigration support on a case-by-case basis
- In-office snacks and meals provided
- Unlimited PTO and company holidays
- In-person team in San Francisco with a collaborative, high-energy environment
Other
- 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