About Company:

Our client is a Palo Alto–based AI infrastructure and talent platform founded in 2018. It helps companies connect with remote software developers using AI-powered vetting and matching technology. Originally branded as the “Intelligent Talent Cloud, "enabled companies to “spin up their engineering dream team in the cloud” by sourcing and managing vetted global talent.

In recent years, they have evolved to support AI infrastructure and AGI workflows, offering services in model training, fine-tuning, and deployment—powered by their internal AI platform, ALAN, and backed by a vast talent network. They reported $300 million in revenue and reached profitability. Their growth is driven by demand for annotated training data from AI labs, including major clients like OpenAI, Google, Anthropic, and Meta.

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Job Title: Movement & Physical Activity Annotator

Location: Pan India

Experience: 3+ yrs.

Employment Type: Contract to hire

Work Mode: Remote

Notice Period: - Immediate joiners

Roles & Responsibilities:

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.

What You'll Do Day-to-Day:





- 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.
- Robust 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.
- Primary: Certified Personal Trainer (CPT) from a recognized organization (e.g., ACE, NASM, ACSM, NSCA), Exercise Physiologist (EP-C, ACSM), or Kinesiologist.
- Secondary (Bonus): Physical Therapist (PT/DPT), Sports Scientist, or a related degree in Exercise Science/Kinesiology.
- Experience: Minimum 2-3 years of practical experience coaching individuals or groups in fitness, rehabilitation, or sports performance.

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