Project Epsilon - Russian Data Trainer

About the role

Project Epsilon

Russian Data Trainer at Welo Global represents a focused opportunity for individuals who possess a strong command of the Russian language and a meticulous approach to detail. In this capacity, you will own the critical validation of data quality by assessing specific visual inputs against textual prompts. The role requires you to own the accuracy of "golden" answers, ensuring that responses are derived solely from observable evidence within the provided images. You will own the consistency of output by adhering strictly to predefined guidelines without deviation. This position owns the responsibility of maintaining high integrity in data labeling for AI training purposes. You will own the task of identifying and flagging any discrepancies between the prompt and the visual source material. This is a task-based, remote-friendly opportunity ideal for individuals who are meticulous, and able to follow detailed instructions consistently while owning the quality of the final dataset.

Key facts

What you'll do

• Examine pre-seeded question and image pairs to determine the correct answer based on visual evidence.
• Provide accurate "golden" answers for Russian language data annotation projects to ensure high-quality training datasets.
• Assess images against prompts to verify content, context, and textual accuracy as part of the data validation workflow.
• Operate within a task-based structure that allows for remote-friendly contribution and complete autonomy over your schedule.
• Apply strict attention to detail to meet the rigorous standards required for AI data annotation and model training.
• Follow complex instructions consistently to maintain dataset integrity and support the development of sophisticated AI systems.
• Identify inconsistencies or errors within the provided image and question sets to prevent the propagation of incorrect data.
• Contribute to large-scale AI data projects by processing tasks efficiently while upholding the highest quality benchmarks.
• Engage with a global community of contributors through a platform that offers responsive guidance and support for remote work.
• Leverage your expertise to influence AI systems that are being built for the Legal field, ensuring real impact through accurate data curation.

Requirements

• You need to be detail-oriented and capable of reviewing pre-seeded questions paired with images to provide accurate "golden" answers.
• You must be able to follow detailed instructions consistently to ensure the accuracy and reliability of the data annotation process.
• You need to own the task of reviewing image-based prompts and answering questions based solely on what is visually observable.
• You must possess the ability to work remotely and manage your own schedule while maintaining high productivity and quality.
• You need to be fluent in Russian to accurately assess language-specific data and provide contextually appropriate answers.
• You must understand the importance of data quality in AI training and be committed to upholding ethical standards in annotation.
• You need to have the capability to identify discrepancies between questions, images, and expected answers to ensure data integrity.
• You must be available to engage with a global contributor community and utilize responsive guidance provided by the platform.

Practical notes

Note: We are looking for detail-oriented Trainers to support an AI data annotation project. In this role, you will review pre-seeded questions paired with images and provide accurate "golden" answers based on what you observe in the image.

This is a task-based, remote-friendly opportunity ideal for individuals who are meticulous, and able to follow detailed instructions consistently.

For Project Epsilon

Russian Data Trainer at Welo Global, What You'll Do.

Review a pre-seeded question along with an accompanying image (e.g., "What is the title of the Excel file based on what you see in the image?").

For Project Epsilon

Russian Data Trainer at Welo Global, Why Join Welo Data?