AI Data Annotation & SQL Specialist — Remote & Flexible

BAM Ventures; New York (NY); Remote; USD 25,000 - 44,000; Full time

Benefits offered by this job

Flexible working hours

Professional development

Remote-first environment

Job summary

Rise Data Labs is a remote-first AI training and data annotation company delivering high-quality labeled data to improve machine learning models. As an AI Data Annotation and SQL Specialist, you will annotate and validate data, while applying SQL to extract and analyze datasets to support training objectives.

You will collaborate with cross-functional teams, bring domain expertise across diverse fields, and ensure precision and consistency in all data labeling tasks.

Qualifications

• Proficiency in SQL and experience with database management.
• Strong attention to detail and commitment to quality assurance.
• Experience in data annotation, labeling, or a related field.
• Ability to work independently and manage multiple projects simultaneously.
• Excellent communication and collaboration skills.

Responsibilities

• Train and improve AI models by annotating and labeling data across various projects.
• Review and validate AI-generated content for accuracy and consistency.
• Leverage SQL skills to extract, manipulate, and analyze data to support training objectives.
• Provide domain expertise to enhance the performance of AI models in different fields.
• Collaborate with cross-functional teams to ensure high-quality data for machine learning applications.

Skills

SQL proficiency

Attention to detail

Data annotation experience

Independent work

Communication skills

Tools

Python

Job description

Rise Data Labs is a remote-first AI training and data annotation company delivering high-quality labeled data to improve machine learning models. As an AI Data Annotation and SQL Specialist, you will annotate and validate data, while applying SQL to extract and analyze datasets to support training objectives.

You will collaborate with cross-functional teams, bring domain expertise across diverse fields, and ensure precision and consistency in all data labeling tasks.