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Part-Time Full-Stack Engineers: Farm-Data Platform Development

Terac · 100% remote · Contract · Posted

Pay
$39/hr
Location
Worldwide
Languages
English
Hours
15 hours per week
Openings
Not listed
Level
Experienced
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Summary

Build and extend a farm-data platform by writing production code, integrating features, and supporting machine learning workflows. Collaborate asynchronously with the team on a long-term basis.

What you'll do

  • Write production-ready code
  • Integrate new features into the core platform
  • Support machine learning workflows
  • Collaborate asynchronously with the team
  • Ensure seamless deployment and system reliability

Requirements

  • Have hands-on experience building complex data platforms
  • Be comfortable managing your own time across any time zone
  • Have a background in full-stack development, software engineering, or machine learning engineering

Skills

  • Full-Stack Development
  • Machine Learning
  • Data Infrastructure
  • Agricultural Technology

Full description

What We're Researching

We're hiring a part-time full-stack engineer to help build across a comprehensive farm-data platform. This permanent role involves developing robust data infrastructure and extending our existing machine learning stack. The work directly supports advanced agricultural analytics and long-term platform growth.

How It Works

You will work remotely on a flexible schedule, committing approximately 15 hours per week to the project. Your responsibilities will include writing production-ready code, integrating new features into the core platform, and supporting machine learning workflows. You will collaborate asynchronously with the rest of the team to ensure seamless deployment and system reliability. This is a long-term engagement expected to last for a year or more, functioning as a permanent team member rather than a short-term contractor.

Who This Is For

We welcome experienced full-stack developers, software engineers, and machine learning engineers looking for part-time, long-term work. The ideal candidate is comfortable managing their own time across any time zone and has hands-on experience building complex data platforms. Professionals with a background in agricultural tech or similar data-heavy industries are strongly encouraged to apply.

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