Computer Vision Engineer

We are looking for a highly hands-on Senior Computer Vision

to take technical ownership of our real-time vision pipeline running on NVIDIA Jetson devices.

This is first and foremost a role for someone who has already built and launched production-grade machine vision systems on Jetson + DeepStream.

About the role:

Our systems operate in real-world logistics environments and process live video streams at the edge. The role includes ownership of a complex pipeline involving detection, tracking, decoding, event logic, integration with surrounding services, and deployment on embedded NVIDIA hardware.

We are looking for someone who knows what it takes to make these systems work outside the lab — under performance constraints, with real cameras, real customers, real failure modes, and real delivery pressure.

Key Responsibilities:

• Own the architecture, quality and evolution of our edge vision pipeline running on
• Jetson + DeepStream.
• Work directly in the code on performance, stability, detection flow, tracking, decoding logic, pipeline design, debugging and production readiness.
• Drive continuous improvement of real-time video processing pipelines, including model integration, tracking, event generation, message flow, and interaction with surrounding system components.
• Take features from concept to production in customer-facing products, with strong attention to robustness, maintainability and field performance.
• Work closely with product, systems, QA and field teams to ensure the solution is practical, testable and deployable in real operational environments.

Requirements:

• Proven hands-on experience building and launching production systems on NVIDIA Jetson and DeepStream
• Strong experience in real-time computer vision / video analytics
• Strong practical experience with C++ and Python
• Experience working on end-to-end edge pipelines, not just training models
• Experience with tracking, detection pipelines, event logic, and system-level debugging
• Experience integrating models and CV logic into production video pipelines
• Strong understanding of performance optimisation on embedded NVIDIA platforms
• Experience debugging real-world issues such as latency, dropped frames, synchronisation problems, memory/resource constraints and long-run stability
• Ability to take ownership of a working but evolving system and improve it pragmatically
• Leadership
• Able to combine hands-on technical execution with ownership, prioritisation and decision-making

Advantage:

• Experience with logistics, warehouse automation, robotics, industrial vision or similar operational environments
• Experience with GStreamer, TensorRT, Triton, MQTT or similar ecosystem components
• Experience with marker-based vision, decoding pipelines, geometry-based logic, or custom vision codes
• Experience deploying and supporting systems in the field
• M.Sc. / Ph.D. in Computer Science, Electrical Engineering or related field

Why join us?

We are building real-world computer vision products for logistics environments, where the challenge is not just model accuracy but making full systems work reliably in production.