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Research Engineer

talentpluto

Remote · Full Time

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Experience
Any
Salary
USD 140,000 – USD 250,000 / year
Openings
1
Posted
8 hours ago
Work mode
Work from home
Resume
Required to apply

Job description

About the Company

Our partner is a YC-backed startup revolutionizing the AI training data sector through an innovative marketplace model. Instead of a traditional labor marketplace, they provide infrastructure enabling data producers to convert their existing datasets into AI-compatible formats and sell directly to AI laboratories. This democratized approach unlocks access to high-quality, valuable data resources, fueling rapid team growth to meet increasing demand.

Job Opportunity

This role is the organization’s highest recruitment priority, tackling a complex research challenge. In a decentralized data marketplace, maintaining data quality at scale poses the chief obstacle to expansion. As a Research Engineer, you will develop automated systems that consistently ensure top-quality data delivery from suppliers to buyers.

Responsibilities

  • Detect and analyze data quality problems such as inconsistencies, format errors, and ingestion difficulties.
  • Conduct initial manual assessments of data to comprehensively understand failure patterns.
  • Create automated quality validation systems leveraging rule-based logic combined with AI methodologies to handle ambiguous cases.
  • Design hybrid review frameworks integrating automation with human oversight where appropriate.
  • Iteratively refine verification techniques to adapt to evolving datasets and advancing AI tools.

Qualifications

  • Highly technical aptitude with rapid learning capability in a dynamic, evolving field.
  • Experience in AI or machine learning engineering, or software engineering within AI-centric companies specializing in data ingestion and processing.
  • Strong analytical reasoning skills for diagnosing potential data quality issues from foundational principles.
  • Comfortable independently managing open-ended, complex problems through all stages.
  • Preferred: Experience handling noisy or unstructured data formats.

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