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.
Reports to: Head of Technology
Location: Taiwan, Remote
What You'll DoAlgorithm Research & Development
- 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
Multi-Sensor Systems Integration
- 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
Applied Engineering & Delivery
- 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
Required
- 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
Valued but Not Required
- 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
- Work on novel computer vision problems most teams never get near — multi-view geometry, 3D reconstruction, and multiple object tracking at production scale
- Help shape the algorithms behind Aurora, our own cloud-managed stereo sensor, from R&D through installations running around the world
- Real ownership over new algorithm development, not just maintenance — your work directly drives what ships next
- Monthly Recharge Day
- Holiday Exchange Program
- Best Self Benefit Program
- Medical Insurance
- Work from Anywhere up to 90 days
Skills Required
- 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
- Experience with embedded or onboard processing on custom hardware
What We Do
RetailNext is the worldwide market leader and expert in retail analytics for brick-and-mortar retail, delivering real-time analytics that enable retailers and manufacturers to collect, analyze, and visualize in-store data. The patent-pending solution uses best-in-class video analytics, Wi-Fi detection, on-shelf sensors, and data from point-of-sale systems and other sources to automatically inform retailers about how people engage with their stores. The highly scalable RetailNext platform easily integrates with promotional calendars, staffing systems, and even weather services to analyze how internal and external factors impact customer shopping patterns – providing retailers the ability to identify opportunities for growth, execute changes, and measure success. RetailNext measures more than one billion shopping trips per year by collecting data from nearly 100,000 sensors in retail stores and analyzing trillions of data points annually. Headquartered in San Jose, CA, RetailNext is a growing global brand operating in more than 40 countries.
