AI Data Labeler

Join the data labeling team at a rapidly growing AI startup!

Are you passionate about shaping the future of AI? Join Reducto (reducto.ai) as an AI Data Labeler, where your work will directly contribute to our platform’s ability to accurately and efficiently ingest data for LLM development. In this role, you’ll help ensure the quality of our datasets by labeling and annotating data while working closely with a talented, fast-growing team.

Your key responsibilities would include:

Daily Tasks:
- Review, label, and annotate datasets (text, tables, images) using specialized tools and software.
- Follow predefined labeling guidelines to ensure consistency and accuracy.
- Perform quality control checks on labeled data to identify errors or inconsistencies.
- Collaborate with tea ---------- mbers to refine data annotation standards and workflows.

Weekly Tasks:
- Communicate with team on labeling and annotation updates and timelines.
- Analyze and summarize patterns or trends in the datasets to help refine machine learning models.
- Work with team to understand the impact of labeled data on model performance.

Qualified candidates for this position will have the following skills and experience:
- Strong attention to detail and ability to follow complex guidelines.
- Experience with handling large datasets and working in fast-paced environments.
- Previous experience with data labeling or annotation is a plus (including experience with tools like Roboflow, Labelbox, Prodigy, Streamlit, or similar).

We are a fast-growing company in the hyper-competitive AI space, so we are looking for candidates that have:
- Strong organizational skills and ability to manage time effectively.
- Excellent communication skills and ability to work collaboratively as part of a remote team.
- Adaptability to changing priorities and eagerness to learn in a fast-moving startup environment.
- Analytical mindset with a focus on problem-solving and critical thinking.
- Excitement about AI and a desire to contribute to innovative projects.

We are seeking candidates to ideally join the team to work full-time, but we are open to candidates looking for part-time work as well. The anticipated salary for a full-time position is $700/month.