Computer Vision Annotator - Contractor

At Sword, we’re building AI to heal billions and unlock humanity’s full potential. In doing so, we’re pioneering AI Care, a fundamentally new approach to healthcare built for medical reasoning, safety, and real-time treatment, not generic technology applied after the fact.

As both a clinical-centric frontier AI lab and an applied AI platform, Sword is reimagining how care is delivered at scale, removing traditional barriers like appointments, waiting rooms, and stigma so more people can access the care they need—and ultimately get back to lives lived in full.

Since 2020, Sword has expanded across physical therapy, women’s health, cardiometabolic, and mental health, and is now moving beyond the session to a fully AI-native, 24/7 care program that brings physical activity, therapeutic exercise, psychotherapy, nutrition, and behavior change into one connected experience.

More than 700,000 members across three continents have completed over 10 million AI sessions, helping 1,000+ enterprise clients avoid more than $1 billion in unnecessary healthcare costs.

Backed by 42 clinical studies, 44+ patents, and more than $500 million raised from leading investors including Khosla Ventures, General Catalyst, and Founders Fund, Sword is defining a new standard for healthcare.

Role

Computer vision models learn from labeled data – they are only as good as the annotations behind them. Your job is to label images and videos of people performing physical exercises, across a range of annotation tasks, using Sword's internal tooling.

This is focused, detail-oriented work that spans multiple annotation types and evolves as our pipelines grow. You are expected to pick up new task types quickly and maintain high consistency across large volumes.

The Data & Tooling team (part of the Algorithms org) builds the labeled datasets that train Sword's proprietary computer vision models. We develop the data foundation that enables our AI to see, understand, and interpret human movement.

What you’ll be doing

Annotating images and videos of people performing physical exercises across a variety of labeling tasks

Reviewing and quality-checking work produced by other annotators

Applying structured guidelines consistently across high volumes

Flagging quality issues, edge cases, and ambiguous content

Adapting to new annotation task types as team needs evolve

Working full-time (40 hours/week), remotely, using Sword's internal and web-based annotation tools

What you need to have

High attention to detail – precision and consistency are the job

Comfortable with high-volume, repetitive digital work for sustained periods

Quick to understand and apply structured guidelines

Experience with data annotation, QA, or content review is a plus

Basic familiarity with human anatomy is helpful but not required (full training provided)

Reliable internet connection and a desktop or laptop computer

No clinical or technical background required