Computer Vision/ML Engineer
- Design, fine-tune, and deploy computer vision models (YOLO, InsightFace, MediaPipe, facial landmark detection, object tracking, pose estimation) for real-time inference on the edge
- Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton
- Build and maintain MLOps pipelines for model training, validation, and performance monitoring
- Develop video processing pipelines that integrate with both classical signal processing and ML based vital sign extraction
- Establish engineering best practices and help reduce technical debt as we scale
- Contribute to the architecture and implementation of the computer vision stack from research to production
- Master's or PhD degree in Machine learning / Computer vision
- Strong fundamentals: data structures, CV algorithms, and systems programming
- Strong C++ skills - this is critical for our edge deployment pipeline
- Solid Python proficiency for ML experimentation and tooling
- Ability to work independently, solve complex problems, and drive projects to completion
- 5+ years experience deploying computer vision models to production, ideally on resource-constrained devices
- Experience with PyTorch and model optimization for edge AI
- Proven ability to take models from research to production on embedded hardware
- Experience with NVIDIA Jetson platform, TensorRT, or Triton Inference Server
- MLOps experience (experiment tracking, model versioning, performance monitoring)
- Experience with sensor fusion (RGB, IR, depth cameras)
- Background in medical devices, regulated environments, or healthcare applications
- Experience working in fast-moving early-stage environments
- Real impact: your code provides care for patients today
- High autonomy and technical ownership - you'll shape our computer vision architecture
- Work at the intersection of cutting-edge AI, edge computing, and healthcare
- A talented, excellent, diverse and international team
- Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing
- Talented, international team tackling meaningful problems in remote patient monitoring
- Competitive salary and equity
- Transparent, mission-driven culture focused on continuous learning
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