Research Scientist, Foundation Models & Data Pipelines

Institute of Foundation Models

Sunnyvale (CA)

Vor Ort

USD 150.000 - 400.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Benefits dieser Stelle

Medical benefits
Dental/vision
401K
Paid time off
Parental leave
Employee assistance
Life insurance
Disability

Zusammenfassung

The Institute of Foundation Models in Sunnyvale, CA is seeking Research Scientists to tackle the data problems that determine our world model capabilities. You will design, develop, and run state-of-the-art systems for curating, ingesting, filtering, annotating, and training with billion-scale visual data.

You will work on motion scoring, camera control, and video understanding, translating human effort into durable automated systems.

Qualifikationen

  • PhD in Machine Learning or Computer Science, or equivalent industry experience.
  • Strong communication and collaboration skills for cross-functional work.
  • Experience building and optimizing large-scale video data pipelines.

Aufgaben

  • Translate requirements into data work for training systems.
  • Design and build scalable data pipelines.
  • Collaborate with engineering to scale data pipelines on AWS and in-house clusters.
  • Develop state-of-the-art visual understanding systems for labeling and annotating media.

Kenntnisse

Data pipeline design
Cross-functional collaboration
Problem solving
Communication skills
Ambiguity navigation
Deep learning systems
Video data understanding

Ausbildung

PhD in ML or CS

Tools

PyTorch

Jobbeschreibung

The Institute of Foundation Models in Sunnyvale, CA is seeking Research Scientists to tackle the data problems that determine our world model capabilities. You will design, develop, and run state-of-the-art systems for curating, ingesting, filtering, annotating, and training with billion-scale visual data.

You will work on motion scoring, camera control, and video understanding, translating human effort into durable automated systems.

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