Materials Science AI Trainer — Remote Data Labeling Leader

Rise Data Labs; United States; Remote; USD 34,000 - 55,000; Full time

Benefits offered by this job

Remote-first

Job summary

Rise Data Labs is a leading AI training and data annotation company seeking a Materials Science AI Training Specialist. You will train and label data for AI models in materials science, review AI outputs, and provide domain expertise to align with industry standards.

You will collaborate with cross-functional teams on diverse projects, ensuring high-quality data for ML applications while contributing to continuous improvement. Our remote-first approach enables experts worldwide to participate.

Qualifications

• Bachelor's or Master's degree in Materials Science, Engineering, or a related field.
• Strong understanding of materials properties, processing methods, and applications.
• Experience in data annotation, labeling, or AI model training.
• Exceptional attention to detail and quality assurance skills.
• Proficient in using annotation tools and software.
• Excellent communication skills, both written and verbal.

Responsibilities

• Train and improve AI models through precise data annotation and labeling in materials science and engineering.
• Review and validate AI-generated content for accuracy and relevance.
• Provide domain expertise to enhance AI model performance and ensure alignment with industry standards.
• Collaborate with cross-functional teams on diverse AI training projects.
• Ensure high-quality data for machine learning applications and contribute to continuous improvement initiatives.

Skills

Data annotation

Attention to detail

Communication

Annotation tools

AI model training

Education

Bachelor's or Master's in Materials Science or Engineering

Tools

Python

MATLAB

Annotation software

Job description

Rise Data Labs is a leading AI training and data annotation company seeking a Materials Science AI Training Specialist. You will train and label data for AI models in materials science, review AI outputs, and provide domain expertise to align with industry standards.

You will collaborate with cross-functional teams on diverse projects, ensuring high-quality data for ML applications while contributing to continuous improvement. Our remote-first approach enables experts worldwide to participate.