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Computer Vision Engineer

Reactive Health
Baladiyat ad Dawhah, QAT
Part-time
Entry
Onsite
Discovered 1 weeks ago
Computer visionHuman pose estimationMotion analysisPythonPyTorchTensorFlow

Full Job Posting

Role overview

ReActive Health is developing a digital platform for workplace musculoskeletal health, including assessments, personalised programmes, clinician approval, exercise tracking, and AI coaching.

The engineer will develop and evaluate video-based movement analysis alongside the Founder and Clinical Lead.

This is a new capability under development; clinical validation is required before making injury-risk claims.

Key responsibilities

  • Build pose-estimation and movement-analysis pipelines for smartphone video.
  • Extract joint angles, movement patterns, and exercise-performance measures.
  • Evaluate accuracy across camera positions, lighting, clothing, and body types.
  • Handle occlusion, low-quality recordings, and uncertain predictions.
  • Work with clinical experts to define annotations, reference measurements, and validation criteria.
  • Integrate tested models into backend and mobile workflows.
  • Implement privacy-conscious video processing and clear confidence thresholds.

Requirements

  • Hands-on experience with computer vision, human pose estimation, or motion analysis.
  • Strong Python skills and experience with PyTorch or TensorFlow.
  • Familiarity with OpenCV and pose-estimation tools such as MediaPipe, MoveNet, or comparable frameworks.
  • Experience preparing datasets, evaluating models, and deploying inference pipelines.
  • Ability to explain model limitations and distinguish movement measurement from clinical risk prediction.
  • Biomechanics, rehabilitation, or mobile-inference experience is advantageous.

Compensation

  • Compensation is equity-based until funding is secured, with no salary before funding.
  • Equity, vesting, milestones, and time commitment will be agreed in writing.
  • Future paid compensation depends on funding and a separate agreement.

Location and working arrangements

  • Location and working arrangements will be discussed during interviews.

Application

  • Applicants are asked to provide a CV and links to relevant projects, repositories, or demonstrations.

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