Data Engineer - Multimodal Systems

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

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Weekend work

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About this role

Data Engineer - Multimodal Systems San Francisco, California, United States Zyphra is an artificial intelligence company based in San Francisco, California. The Role: 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. You'll Work Across: - 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 What We're Looking For / 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. Qualifications / Additional Skills: - 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

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