Movement & Physical Activity Annotator

Position: Movement & Physical Activity Annotator
Employment Type:Contract (2 months)
Location: Remote
YOE: 2+ Years
Availability - 8 hours per day with an overlap of 4 hours with PST.

Role Overview:
We are seeking experienced Movement & Physical Activity Experts to help evaluate and enhance large language model (LLM) outputs related to human movement, physical activity, and exercise science. You’ll assess AI-generated content for scientific accuracy, safety, and relevance — contributing to the development of responsible AI in health and fitness. Selected talents will review and label data related to physical activity, exercise, and movement patterns (e.g., wearable sensor data, activity logs, video, or text) to support the training and evaluation of AI/health models.

Key Responsibilities:

• Annotate activity type, intensity, duration, and movement quality from raw data sources (sensor streams, logs, video, or transcripts).
• Apply standardized taxonomies (e.g., MET values, exercise categories, gait/posture labels) consistently across datasets.
• Flag ambiguous, incomplete, or low-quality data for review.
• Identify inconsistencies between self-reported activity and objective data signals.
• Collaborate with domain experts to refine annotation guidelines and edge-case handling.
• Meet accuracy and throughput targets while maintaining inter-annotator agreement.

Requirements:

• Background in exercise science, kinesiology, physical therapy, sports science, or related field.
• Familiarity with physical activity classification systems and wearable/sensor data.
• Strong attention to detail and ability to follow detailed labeling guidelines.
• Comfort working with spreadsheets, annotation tools, or labeling platforms.
• Ideal to have a MacBook.

Preferred Qualifications:

• Prior data annotation or labeling experience, especially in health/fitness domains.
• Experience with wearable device data (e.g., accelerometer, heart rate, GPS).
• Basic understanding of AI/ML data pipelines.

Pay: Up to $40,000.00 per month

Work Location: Remote