Computer Vision Engineer

About Us:

RetailNext is the global leader in brick-and-mortar retail analytics, tracking over a billion shopping trips annually across 100,000+ sensors worldwide. Our Aurora sensor combines edge-based video analytics, IoT, and AI to deliver real-time insights for Fortune 500 retailers.

The Computer Vision & ML Research team develops and deploys algorithms for object detection, tracking, and sensor fusion - optimized for resource-constrained edge devices. We work with IoT engineers and cloud services to deploy solutions across 100+ countries.

The Role:

We seek a software engineer passionate about deploying and optimizing computer vision and ML solutions on edge devices, in addition to supporting data infrastructure and annotation tooling. Your work will directly impact hundreds of thousands of sensors globally.

In this role, you will collaborate on:

• Solving deployment challenges (latency, memory, and power constraints) for edge-based CV/ML.
• Shipping code that runs at scale - your work directly impacts millions of daily inferences.
• Maintaining robust data foundations (efficient labeling workflows, validation tools) to sustain model accuracy.

Responsibilities:

• Profile and deploy neural networks (TFLite, OpenVINO) for edge devices.
• Develop and optimize C++ code for real-time performance (SIMD, multithreading, OpenMP).
• Transition prototypes to production, implementing hardware acceleration (GPU/DSP/NPU) and memory-efficient inference pipelines.
• Optimize CV pipelines for third-party IP cameras.
• Maintain and improve annotation infrastructure (CVAT, automation tools) to support model iteration.

Qualifications:

Must-have:

• Strong C++ for performance-critical systems.
• Experience with ML deployment (TFLite, OpenVINO, ONNX).
• Comfort with Linux, Docker, and CI/CD basics.

Nice-to-have:

• Parallel computing (OpenCL, OpenMP) or edge/IoT systems.
• Familiarity with CV/Video frameworks (OpenCV, FFMpeg), and Python for scripting.
• Exposure to data annotation tools (CVAT, Label Studio) or pipeline optimization.

Why Join Us:

• Deploy CV/ML systems at scale (billions of inferences/month).
• Hybrid role: Focus on low-level optimization with secondary work on data infrastructure.
• Remote role with smart, small-team dynamics.

What's it like to work here?

• Remote Work

• 90-Day Work Anywhere: Work from anywhere for 90 days yearly.

• Autonomy & Growth: Flexible schedules, ownership, career investment.

• Customer Obsessed: Everything we do is for our clients.

Perks & Benefits

• Best Self Allowance: Annual stipend for personal growth.

• Recharge Days: Monthly company-wide day off.

• Career Growth: We invest in you.