Principal Engineer, Computer Vision & Edge AI

QQR Labs, the technology arm of QQR Freight, is hiring its first engineer to build a computer vision and edge AI product for physical freight. The role owns the product end to end, including field hardware, on-device models, data platform and engine, and fleet tooling.

Responsibilities:

• Ruggedized capture hardware: industrial cameras, IR illumination, Jetson-class GPU compute, cellular backhaul, weatherproof enclosures built for unattended outdoor duty
• On-device ML: detection, classification, and OCR on vehicles at highway speed, day and night
• The data platform: high-volume ingestion, entity resolution, search, alerting, APIs
• The data engine: auto-labeling pipelines, continuous retraining, and evaluation loops fed by real-world captures
• Fleet tooling: provisioning, over-the-air updates, and health monitoring for hardware deployed far from a desk

Requirements:

• You have shipped computer vision on real hardware in the real world, not just in a notebook. Detection, tracking, OCR, deployed where weather, vibration, and glare live
• A camera-first mindset: multi-camera perception, vision-only stacks, and models that hold up in rain, glare, and darkness
• Edge and embedded fluency: Linux on ARM, camera pipelines (GStreamer or similar), model optimization (TensorRT, ONNX, quantization)
• Cloud and data competence: Python, AWS or GCP, streaming ingestion, practical MLOps
• You make hardware decisions, work without a playbook, and own outcomes
• If you have built vision systems that live outdoors or on vehicles at scale, you already know this class of problem. Come build one where you hold real skin in the game