Design and implement computer vision systems that power autonomous healthcare robots, enabling real-time patient monitoring in clinical environments. This role plays a central part in advancing an AI-driven sensing platform that helps alleviate pressure on healthcare systems worldwide.
What You'll Do
- Develop, refine, and deploy computer vision models—including object detection, facial analysis, pose estimation, and tracking—for low-latency inference on embedded devices
- Optimize deep learning models using quantization, pruning, and inference engines like TensorRT and NVIDIA Triton to meet strict hardware constraints
- Build robust MLOps pipelines to manage model training, evaluation, versioning, and performance tracking across the lifecycle
- Design video processing workflows that combine classical signal processing with machine learning to extract vital signs from multimodal sensor inputs
- Lead the evolution of the computer vision architecture, ensuring scalability, maintainability, and adherence to engineering best practices
- Collaborate across research and engineering to transition prototypes into reliable, production-grade systems
Requirements
- Master’s or PhD in Machine Learning, Computer Vision, or a closely related field
- Solid foundation in data structures, computer vision algorithms, and systems-level programming
- Proficiency in C++, essential for developing high-performance components in edge deployment pipelines
- Strong Python skills for prototyping, tool development, and ML experimentation
- Minimum of five years of experience deploying computer vision models in production, particularly on resource-limited hardware
- Hands-on experience with PyTorch and techniques for edge AI optimization
- Demonstrated ability to independently lead technical projects from concept to deployment
Preferred Qualifications
- Familiarity with NVIDIA Jetson, TensorRT, or Triton Inference Server
- Experience with MLOps tools for experiment tracking, model registry, and monitoring
- Background in sensor fusion using RGB, infrared, and depth cameras
- Exposure to medical devices, healthcare applications, or regulated environments
- Experience in fast-paced, early-stage technology environments
Benefits
- Direct impact—your work powers systems that support patient care today
- High level of autonomy and ownership over technical direction and architecture
- Opportunity to work at the intersection of edge AI, robotics, and healthcare innovation
- Join a diverse, international team solving meaningful problems in remote patient monitoring
- Competitive compensation with salary and equity
- Culture of transparency, continuous learning, and mission-driven development
