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Hayden AI deploys embedded computer vision systems on city infrastructure to analyze traffic and street safety in real time. The stack—PyTorch, TensorFlow, NVIDIA Jetson, LIDAR, GNSS, and custom C++ inference pipelines—reflects a company solving hard edge-AI problems: perception at the network edge, GPS-denied localization, and sub-100ms latency constraints. Hiring is engineering-heavy (14 of 16 active roles) with concentrated seniority (8 senior, 3 staff, 1 principal), indicating active scaling of core perception and embedded systems teams while tackling production stability and multi-region cloud infrastructure challenges.
Tech Stack 55 technologies
Core StackC++ PyTorch TensorFlow AWS Docker Kubernetes Python React JavaScript TypeScript Go PostgreSQL MySQL AWS RDS Pandas GCP Azure Amazon Cognito Kalman Filter LIDAR NVIDIA Jetson GNSS V4L2 GStreamer OpenCV TensorRT CUDA ONNX Runtime Embedded Linux NVIDIA Nsight+25 more
What Hayden AI Is Building
◆Challenges
- Transitioning research prototypes to production
- Scaling pilot initiatives
- Ensuring reliable, high-performance operation of edge ai systems
- Optimizing edge inference performance
- Robust perception in gps-challenged environments
- Production stability issues
- Complex program management
- Scaling engineering organization
- Cross-functional coordination
- Scaling multi-region cloud
▲Active Projects
- Real-time perception pipelines
- Next-generation perception systems
- State-of-the-art ml and cv models
- Operational scaling initiatives
- Field verification
- Multi-modal vlm fine-tuning for domain adaptation
- Advanced mapping, localization, and slam solutions for embedded camera systems
- Next generation portal platform
- Developer processing improvement
- Prototype perception systems
Hiring Activity
15 roles · 10 in 30d
Department
Seniority
Company intelligence