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Research Engineer - Multimodal Data

Eventual ComputingSan Francisco
On-site Full-time

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Experience Level

Entry Level

Qualifications

Candidates should possess a strong background in computer vision, machine learning, and data processing. Experience with vision-language models, data annotation techniques, and familiarity with multimodal datasets are highly desirable. A Bachelor's degree in a related field or equivalent practical experience is required.

About the job

Eventual Computing builds tools that help AI teams work with large, complex datasets. Based in San Francisco, the company supports projects in robotics, autonomous vehicles, and advanced video generation. Its open-source engine, Daft, is already in use at organizations with demanding data needs. The team focuses on making data curation and model training more efficient, so the right datasets are always within reach.

The office is located in the Mission district, where collaboration with leading AI labs and infrastructure companies is part of daily work.

Role overview

The Research Engineer - Multimodal Data will join the Visual Understanding team. This position centers on building solutions to make vast amounts of video and sensor data accessible and easy to query. The work directly supports researchers who need to find and use specific datasets quickly.

What you will do

  • Develop and refine systems that process petabytes of multimodal data, including video and sensor streams.
  • Apply vision-language models to improve how data is discovered and retrieved.
  • Define and influence the roadmap for visual understanding features.
  • Train models to streamline large-scale data annotation and improve efficiency for research teams.

About Eventual Computing

Eventual Computing is transforming the landscape of Physical AI through advanced data solutions. With significant backing and a talented team, we are committed to facilitating rapid advancements in AI technology.

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