ML Vision Engineer

We're looking for a Machine Learning Vision Engineer to help our R&D team push the boundaries of video analytics — from multi-view geometry and 3D reconstruction to multiple object tracking and facial analysis. You'll work at the core of Aurora, our own cloud-managed stereo sensor, which combines onboard shopper detection and tracking with WiFi, Bluetooth, and HD video recording.

You'll do well here if you have a strong grip on multi-view geometry, an inventive eye for new techniques, and a genuine drive to scale computer vision into large, real-world installations. This isn't research in a vacuum — the algorithms you build run in stores around the world.

Because RetailNext builds its own hardware and software end to end, you'll get a rare shot at owning problems from theory through production deployment.

• →Lead the development of new computer vision algorithms for shopper detection, tracking, and analytics
• →Improve the performance and efficiency of existing algorithms already running in production
• →Apply multi-view geometry techniques to solve image registration, mosaicking, and 3D reconstruction problems
• →Prototype new approaches quickly in Python or MATLAB before hardening them for production
• →Stay close to the research space so RetailNext's techniques keep pace with — and get ahead of — the field

• Build robust software that integrates multiple sensors and tracking systems, including Aurora's stereo cameras, WiFi, and Bluetooth
• Design for real-world conditions — variable lighting, store layouts, and hardware constraints — not just clean lab data
• Work across the video, WiFi, and Bluetooth analytics pipelines to keep detection and tracking accurate and consistent

• Design, implement, validate, and release applications and capabilities in C++ and Python
• Take algorithms from prototype to production-ready code that runs reliably at scale
• Validate new techniques against real deployments across large, global installations
• Partner with the rest of the R&D team to review, test, and ship new capabilities

• Master's degree in Computer Science, Computer Vision, or Machine Learning
• Strong programming skills in C/C++
• Rapid prototyping experience in Python or MATLAB
• Strong understanding of multi-view geometry
• Experience designing, implementing, and releasing computer vision applications

• Experience with multiple object tracking or facial analysis
• Experience integrating multi-sensor systems (video, WiFi, Bluetooth)
• Background applying computer vision at production scale, not just in research
• Experience with embedded or onboard processing on custom hardware