Member of Technical Staff (Data Intelligence)

Reka

WorldwideFully remoteFull TimeSeniorInformation Technology
Posted 3mo ago

Why we think you can apply

Hiring model
Open worldwide · the employer states no country restriction
Work from
Anywhere, the UAE included

Posted 3 months ago · apply link checked 6 hours ago

About the role

Responsibilities

  • Work with model researchers to define data quality metrics, validation checks, and acceptance thresholds
  • Explore open source datasets and create internal datasets for building fundamental World Models
  • Build algorithms for automated data quality assessment, data domain mixtures, and domain adaptation
  • Track datasets, metadata, provenance, and versions to ensure reproducible experiments
  • Own CI/CD and development tooling for the data stack including GitHub, Python, and PyTorch
  • Track and optimize throughput, storage, and compute utilization across pipelines

Requirements

  • Strong ML and deep learning fundamentals
  • Experience building and operating large-scale data or compute systems
  • Demonstrated research experience with data compositions, quality, and dataset releases
  • Practical experience with distributed processing and orchestration such as Spark, Ray, or Airflow
  • Solid Python skills and familiarity with modern model training workflows
  • Ability to design and execute experiments with unbiased outcomes

Preferred Qualifications

  • Experience with large video datasets
  • Experience with dataset curation for training
  • Experience building internal tooling for evaluation or analysis in ML environments

Benefits

  • 5 weeks of paid leave
  • Comprehensive healthcare benefits including vision and dental
  • Visa assistance (H1B and OPT transfers for US employees)

About the Company

Reka is a globally distributed foundation model startup headquartered in the San Francisco Bay Area. The mission is to build useful multimodal artificial intelligence to empower organizations and businesses.

What we look for

  • ML and deep learning fundamentals
  • Large-scale data/compute systems experience
  • Distributed processing (Spark, Ray, Airflow)
  • Solid Python skills
  • Research experience with data quality
PythonMachine LearningPyTorch
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