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仕事内容
About the Role
This position is for a remote Linux/Ubuntu AI Trainer working on an hourly basis to assist AI data training efforts. The role requires carrying out structured and detail-focused tasks, including installing software on a personal Ubuntu/Linux machine and accurately recording actions while completing assignments. Candidates do not need deep AI expertise but must be tech-savvy, reliable, attentive to detail, and able to work autonomously. This opportunity suits students, junior candidates, or tech-enthusiasts experienced with Ubuntu/Linux environments and patient with repetitive work.
By joining, you contribute to enhancing AI models used worldwide across various industries through a fast-growing AI data services firm servicing leading AI companies and foundational model developers.
Responsibilities
- Carefully adhere to extensive written instructions to complete tasks.
- Install and operate necessary applications on Ubuntu/Linux systems.
- Review work output for errors prior to submission.
- Report inconsistencies, unclear guidance, or software issues promptly.
- Maintain concentration and accuracy during repetitive or intricate assignments.
- Complete work aligned with the agreed 15 hours per week availability.
- Communicate efficiently with the project team to request support when needed.
- Help improve the precision of AI training data sets for enhanced model development.
Candidate Profile and Requirements
- Own a computer running Ubuntu/Linux OS.
- Comfortable installing project-required apps, tools, and software independently.
- Possess basic computer skills, including browser-based tool usage.
- Capable of following detailed written instructions consistently.
- Detail-focused, patient, and able to maintain attention throughout tasks.
- Reliable, punctual, and able to meet set deadlines.
- Students and junior-level applicants are encouraged to apply.
- Prior exposure to AI data training, annotation, QA, software testing, or research tasks is advantageous but not mandatory.
- Availability to commit approximately 15 hours weekly.