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Data Engineer (Volunteer)

  • Remote, United States

Remote

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Job details

Workplace
Remote
Posting language
English

Original job description

Role ID: TAIRC-ROLE-019 Department: Applied AI Engineering Engagement Type: Volunteer (unpaid) Work Arrangement: Remote. Working hours are aligned to US Eastern Time (EST/EDT); the exact schedule is agreed with your supervisor at onboarding. Duration and Time: Initial 6-month volunteer term, which may be extended by mutual agreement. Weekly time commitment is agreed at onboarding and should be realistic for you. Compensation: Unpaid volunteer opportunity. TAIRC is currently in a pre-funding stage and is building its funding base. No salary, stipend, or other compensation is offered at this stage. Supervision: Review and guidance from the Director of Engineering (TAIRC-ROLE-003) or a designated engineering lead, confirmed at onboarding. About TAIRC The AI Research Center, Inc. (TAIRC) is a nonprofit research organization advancing transparent evaluation, responsible governance, and public-interest AI infrastructure. Our work focuses on helping institutions and communities better understand AI systems, evaluate their limitations, and translate research into responsible practice. TAIRC connects technical research with public communication, accessibility, governance, and human accountability. We aim to make AI research more transparent, understandable, and useful for the public good. This position is with TAIRC, not Metasys. Metasys supports the recruitment and administrative process on behalf of TAIRC. Position Overview Data Engineers build and maintain data pipelines for training and analysis. This description follows the role as published on tairc.com/careers. This position is with TAIRC, not Metasys. TAIRC's published research agenda does not mean that every program is funded, staffed, or complete. Specific assignments are confirmed at onboarding, and volunteer work is not presented as approved TAIRC research or institutional findings until it has been reviewed.

Responsibilities

  • Assemble large datasets.
  • Improve the reliability of data ingestion and processing.
  • Build ETL infrastructure for structured and unstructured data.
  • Develop analytical tools for stakeholders.
  • Work with cross-functional teams on data quality.

Qualifications

  • A bachelor's degree in computer science or a related field.
  • Experience with data warehousing, databases, and big data technologies.
  • Ability to work remotely during US Eastern Time (EST/EDT) hours and to collaborate asynchronously with a distributed team.
  • Understanding and acceptance that this is an unpaid volunteer opportunity at this stage.

Engagement and Compensation Disclosure TAIRC is currently building its funding base. This is a volunteer opportunity, and no salary, stipend, or other compensation is offered at this stage. Any future paid appointment would depend on available funding, organizational approval, applicable legal compliance, and a separate written agreement. Participation does not guarantee future employment or compensation. This is a volunteer contribution, not an employment relationship or a formal educational internship. Volunteers contribute by choice, may step back at any time with reasonable notice, and are asked to keep time commitments realistic. Applicants who need academic credit may inquire, but credit is not guaranteed and would require a separate arrangement with their institution. Equal Opportunity and Accessibility TAIRC evaluates candidates based on role-related skills, relevant experience, and documented review criteria. Decisions must not be based on protected personal characteristics. Applicants who need an accommodation or an alternative application format may contact hr@tairc.com. How to Express Interest Candidates interested in contributing to TAIRC's data engineering work may contact hr@tairc.com with questions about the opportunity.

More about this job

Skills

  • Data engineering
  • Data models
  • Cleaning
  • Statistical quality control
  • Data warehousing
  • Computer science
  • Python
  • SQL
  • Problem solving
  • AWS
  • Google Cloud
  • Microsoft Azure
  • Git
  • Apply information security policies

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