Edge CV Engineer: Real-Time Multi-Camera Tracking

Zillion Technologies, Inc.; United States; On-site; USD 96,000 - 117,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Job summary

Zillion Technologies, Inc. is seeking a Computer Vision Engineer to own the entire CV effort on edge devices and GPU servers. You will deploy real-time pipelines on NVIDIA Jetson hardware, handle person and intent detection, and multi-camera tracking in public and commercial spaces.

You will build training and deployment pipelines, optimize performance for edge inference, and work with RTSP streams and cross-camera re-identification to anchor detections in physical space.

Qualifications

• 5+ years of hands-on computer vision engineering experience.
• 2+ years deploying models to production edge hardware.
• Proficiency with PyTorch for training and ONNX/TensorRT for inference.
• Experience building multi-object tracking pipelines.
• Strong Python and C++ skills; comfortable with GStreamer pipelines.
• Experience with NVIDIA GPU tooling and JetPack/Jetson ecosystem.
• Experience annotating data and preparing datasets for custom detections.
• Familiarity with RTSP streams, Linux environments, and video codecs.
• Cross-camera re-identification and zone/space analytics experience.

Responsibilities

• Own end-to-end computer vision engineering on edge devices and GPU servers.
• Develop systems for person/intent detection and multi-camera tracking.
• Build training and deployment pipelines; optimize edge inference performance.
• Work with RTSP streams and cross-camera fusion to anchor detections in space.

Skills

Computer vision

Edge deployment

Python

C++

GStreamer

CUDA

cuDNN

TensorRT

PyTorch

ONNX

Tracking

Linux

Tools

YOLO detectors

JetPack/Jetson SDK

OpenCV

GStreamer

Job description

Zillion Technologies, Inc. is seeking a Computer Vision Engineer to own the entire CV effort on edge devices and GPU servers. You will deploy real-time pipelines on NVIDIA Jetson hardware, handle person and intent detection, and multi-camera tracking in public and commercial spaces.

You will build training and deployment pipelines, optimize performance for edge inference, and work with RTSP streams and cross-camera re-identification to anchor detections in physical space.