Join a forward-thinking team building AI-powered sensing technology for autonomous healthcare robots. In this role, you'll lead the development and deployment of real-time computer vision models on edge hardware, enabling non-invasive patient monitoring in live clinical environments. Your work will directly support clinical assessments by powering intelligent systems that operate safely and efficiently in real-world medical settings.
What You'll Do
- Design, 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 acceleration frameworks like TensorRT and NVIDIA Triton
- Build and maintain scalable MLOps pipelines for training, validation, and ongoing model performance tracking
- Develop robust video processing workflows that combine classical signal processing with machine learning for vital sign extraction
- Guide best practices in software engineering and help manage technical scalability as the system grows
- Lead the evolution of the computer vision stack from prototyping through to production deployment
What We're Looking For
- Advanced degree in computer vision, machine learning, or a closely related technical field
- Solid grasp of data structures, computer vision algorithms, and systems-level programming
- Strong proficiency in C++, essential for performance-critical edge deployment
- Fluency in Python for machine learning experimentation and tool development
- Proven experience shipping computer vision models into production, especially on resource-limited hardware
- Hands-on experience with PyTorch and optimizing models for edge AI applications
- Ability to lead technical direction and independently drive complex projects from concept to deployment
Nice to Have
- Experience with NVIDIA Jetson, TensorRT, or Triton Inference Server
- Background in MLOps—experiment tracking, model versioning, monitoring
- Familiarity with sensor fusion across RGB, infrared, and depth cameras
- Exposure to medical devices, regulated industries, or healthcare technology
- Experience in fast-moving, early-stage environments
Why This Matters
Your work will power intelligent systems that monitor patients without physical contact, improving care delivery in real healthcare facilities. You’ll operate at the intersection of edge computing, robotics, and multimodal AI, with full ownership over critical architecture decisions. The team is international, technically deep, and committed to solving meaningful challenges in remote patient monitoring.
We offer competitive compensation, equity, and a culture rooted in transparency, continuous growth, and shipping technology that makes a difference.
