Senior Computer Vision / ML Engineer

About Us

We combine computer-vision assessments, wearable integrations, and personalized content to help people move better. We’ve already shipped real-time overhead squat analysis to thousands of users across our mobile Android & iOS and our Enterprise iPad apps. Next up: an on-device Single-Leg Balance test that quantifies sway, stability, and compensations within seconds.

The Challenge You’ll Own

Lead the end-to-end R&D, model training, and production deployment of our single-leg balance assessment pipeline—from raw video capture to interpretable scores surfaced in SwiftUI & Kotlin.

Research & Metric Design

• Define clinically relevant KPIs (center-of-mass sway, time-to-failure, hip strategy classification, knee stability, etc.).
• Translate research papers and PT standards (e.g., Y-Balance, CTSIB) into algorithmic requirements.

Data Pipeline

• Drive collection strategy (camera angles, frame rate, subject diversity) and labeling guidelines.
• Set up annotation workflows in CVAT or Labelbox.
• Automate quality control and inter-rater reliability checks.

Modeling & Signal Processing

• Evaluate pose-estimation backbones such as Google ML Kit Pose, MediaPipe, OpenPose, and custom Core ML models.
• Prototype sway-trajectory filters, spectral analysis, and compensation heuristics using Python and NumPy.
• Train and benchmark lightweight models suitable for on-device inference on iOS (A12–A17) and Android (Snapdragon 845+).

Edge Deployment

• Convert models to Core ML or TensorFlow Lite with quantization and accelerator delegates (Neural Engine, GPU, Hexagon DSP).
• Integrate models into the existing Assessment Engine SDK.
• Expose clean Swift and Java wrappers and sample unit tests.

Accuracy & Performance Validation

• Establish gold-standard benchmarks using force-plate or motion-capture ground truth.
• Meet target performance: latency under 100 ms/frame, minimal battery drain, and model footprint under 30 MB.

Collaboration & Documentation

• Publish technical specifications, experiment logs, and API documentation for frontend, product, and external teams.
• Collaborate closely with iOS, Android, and backend engineers.

Tools & Technologies You’ll Work With

R&D:

• Python, Jupyter, NumPy, PyTorch, TensorFlow
• OpenCV, SciPy, pandas
• AWS Sagemaker or custom GPU rigs
• CVAT, Labelbox, Weights & Biases

Production:

• Core ML, ML Kit, MediaPipe
• Swift, Kotlin
• C++/Metal (for micro-optimizations)
• Assessment Engine SDK
• GitHub Actions, Fastlane, Bitrise

Must-Have Qualifications

• 4+ years building and deploying CV/ML models for pose, action recognition, or biomechanics.
• Shipped at least one model on-device (Core ML, TFLite, NNAPI, or similar) with strict latency and size requirements.
• Strong foundation in linear algebra and signal processing; capable of implementing filters and kinematic metrics.
• Experience designing data-collection protocols and managing annotation quality.
• Solid software engineering practices: version control, code reviews, automated tests, and clear English documentation.

Nice-to-Haves

• Experience in rehab, sports science, or digital therapeutics.
• Familiarity with Rook wearable SDK, HealthKit, or aligning CV metrics with physiological data.
• Knowledge of 3D pose estimation (dual-cam or monocular) and sensor fusion techniques.
• Contributions to open-source computer vision or machine learning frameworks.