Senior AI Trainer

micro1; United States; Remote; USD 55,000 - 96,000; Full time

Job summary

micro1 is seeking a Senior AI Trainer contractor to collaborate on a customer‑driven project that enhances AI system accuracy through expert‑level video annotation and data labeling. Remote work with flexible scheduling is offered, contributing to high‑quality, frame‑accurate data for model training.

You will review robotic arm footage, apply grading guidelines, and tag events with precise timestamps, ensuring rigorous data quality while coordinating with project trainers and other contributors.

Qualifications

• Excellent attention to detail and accuracy in reviewing and tagging visual data.
• Strong written and verbal communication for collaboration, reporting, and updates on progress and challenges.
• Demonstrated time management and self-organization abilities for remote project participation.
• Analytical and problem-solving mindset with a proactive approach to annotation challenges.

Responsibilities

• Review video footage of robotic arms executing tasks, identifying key actions and outcomes with precision.
• Apply detailed grading guidelines to tag and annotate events, providing structured observations to improve model performance.
• Mark precise timestamps for the start and end of key actions, ensuring frame-accurate segmentation of each video session.
• Verify timestamp accuracy and alignment across annotations, correcting drift between labeled events and footage.
• Utilize video annotation tools to record findings and submit annotated datasets in alignment with project standards.
• Collaborate with project trainers to resolve ambiguities and ensure annotation consistency.
• Participate in ongoing quality reviews to maintain rigorous annotation standards.

Skills

Attention to detail

Communication

Time management

Analytical mindset

Tools

Video annotation tools

Timeline-based interfaces

Job description

Senior AI Trainer Role Type: Contractor Location: Remote micro1 is engaging Senior AI Trainers to collaborate on a customer-driven project enhancing AI system accuracy through expert-level video annotation and data labeling. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities:

• Review video footage of robotic arms executing assigned tasks, identifying key actions and outcomes with precision.
• Apply detailed grading guidelines to accurately tag and annotate events, providing structured observations that improve model performance.
• Mark precise timestamps for the start and end of key actions, transitions, and outcomes, ensuring frame-accurate segmentation of each video session.
• Verify timestamp accuracy and alignment across annotations, correcting drift or inconsistencies between labeled events and the underlying footage.
• Utilize video annotation tools and platforms to record findings and submit annotated datasets in alignment with project standards and milestones.
• Collaborate with project trainers and contributors to resolve ambiguities, refine guidelines, and ensure annotation consistency across the team.
• Participate in ongoing quality reviews, incorporating feedback to maintain rigorous annotation standards.

Required Skills and Qualifications:

• Exceptional attention to detail and accuracy in reviewing and tagging visual data.
• Strong written and verbal communication skills for effective collaboration, reporting, and timely updates on progress and challenges.
• Demonstrated time management and self-organization abilities for independent, remote project participation.
• Analytical and problem-solving mindset, with a proactive approach to resolving annotation challenges.

Preferred Qualifications:

• Proven experience with video annotation, data labeling, or similar data-centric annotation projects.
• Familiarity with video annotation tools and software platforms, including timeline-based interfaces for timestamping and event segmentation.
• Experience with frame-level or timecode-based annotation (e.g., marking event boundaries, working with frame rates, or reviewing footage frame by frame).
• Background in AI training, machine learning data preparation, or robotics projects (strongly preferred).

Originally posted on Himalayas