About the job
Vivacity Labs develops technology to help authorities worldwide monitor and manage real-time traffic, aiming to make transport systems safer and more sustainable. The team’s work supports cities and organizations seeking better traffic insights and control.
Role overview
The Computer Vision Engineer will contribute to the core computer vision stack, focusing on real-time traffic analytics built with NVIDIA Edge AI. The role involves developing, maintaining, and deploying AI-powered traffic sensor systems, with particular attention to performance, accuracy, and efficiency. These efforts support Vivacity’s GStreamer and DeepStream-based pipelines.
Collaboration is a key part of this position. The engineer will work closely with researchers and hardware engineers to ensure that deployed models run reliably in production. There is also the opportunity to take ownership of significant components within the vision stack and influence the direction of Vivacity’s edge AI systems.
Key responsibilities
- Advance DeepStream and GStreamer pipelines, add new features, and deploy advanced deep learning models (approximately 75% of the role)
- Debug and support production systems as needed (about 15%)
- Collaborate with teams such as cloud engineers and data specialists on projects like self-learning algorithms and dashboards for new datasets (about 10%)
Location and working arrangements
This position is based at the London office near Old Street. Flexible and hybrid working options are available. Wednesdays in-office are required, and two days per week in-person are recommended.
Reporting line
This role reports to Adam Fry, Engineering Manager, Sensor Hardware & Electronics.
Compensation
Salary: £55,000–£70,000
Vivacity Labs is open to applicants outside this salary range and will discuss the compensation package based on experience and expertise.

