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Hayden AI builds embedded vision systems that process urban scenes in real-time on vehicle-mounted hardware. The stack is heavily ML-focused (PyTorch, TensorFlow, OpenCV, CUDA, NVIDIA Jetson) with a clear edge-to-cloud architecture (Docker, Kubernetes, AWS) — indicating a company shipping perception models to resource-constrained devices, then syncing insights back to central analytics. Active hiring is concentrated in engineering (14 roles, mostly senior-level), with acute pain points around scaling delivery operations and cost efficiency, suggesting they're in the phase of moving from prototype to city-wide rollouts.
Tech Stack 54 technologies
Core StackPyTorch TensorFlow Python Pandas C++ AWS Java InfluxDB Redshift Grafana Datadog Postman Jenkins GitHub Actions GitLab CI/CD Docker Kubernetes Terraform OpenCV TensorRT CUDA NVIDIA Jetson ONNX Runtime Embedded Linux NVIDIA Nsight Pytest TestNG REST Assured SQL AWS SQS+24 more
What Hayden AI Is Building
◆Challenges
- Scaling organization
- Protecting customer data from cyber threats
- Cost efficiency
- Scaling service delivery operations
- Improving employee data accuracy
- Cross-functional coordination
- Resource constrained systems
- Building scalable codebase
- Cloud-native system validation
- Data pipeline accuracy
▲Active Projects
- Real-time cv/ml pipelines
- Train deep learning model c
- Gps data analysis
- Edge ai hardware product development
- All hands meeting coordination
- People ops process improvement projects
- Cutting-edge perception system
- Real-time urban scene perception
- Cloud/device integration of perception models
- Advanced mapping, localization, and slam solutions for embedded camera systems
Hiring Activity
20 roles · 10 in 30d
Department
Seniority
Company intelligence
