Remote Computer Vision Engineer - AI/Video Analytics

Bright Vision Technologies; Sunnyvale (CA); Remote; USD 115,000 - 165,000; Full time

Job summary

Bright Vision Technologies is seeking a Computer Vision Engineer to develop image and video analysis solutions for enterprise applications. The engineer will prepare visual datasets, build and evaluate computer vision models, and integrate reliable visual intelligence into production systems.

Collaborate with software and data teams, optimize inference workflows, and contribute to scalable ML deployments while adhering to best practices in model deployment and API integration.

Qualifications

• 5+ years in computer vision, ML, or image-processing engineering.
• Strong Python programming and OpenCV expertise.
• Hands-on PyTorch or TensorFlow for vision models.
• Knowledge of image classification, object detection, segmentation, and metrics.
• Experience with dataset preparation, augmentation, and validation.
• Familiar with REST APIs, Git, and software testing practices.
• Strong analytical, debugging, and communication skills.
• Experience in iterative software delivery and release validation.

Responsibilities

• Develop CV pipelines for image classification, object detection, segmentation, or visual inspection.
• Prepare, annotate, validate, and augment image/video datasets.
• Train, fine-tune, and evaluate models using task-specific metrics.
• Optimize model inference for accuracy, throughput, latency, and deployment constraints.
• Integrate vision models into APIs, batch workflows, or edge environments and document performance.

Skills

Python

OpenCV

PyTorch

TensorFlow

Data augmentation

REST APIs

Git

Model evaluation

Image processing

Communication skills

Tools

YOLO

Detectron2

torchvision

ONNX

TensorRT

GPU inference

Job description

Bright Vision Technologies is seeking a Computer Vision Engineer to develop image and video analysis solutions for enterprise applications. The engineer will prepare visual datasets, build and evaluate computer vision models, and integrate reliable visual intelligence into production systems.

Collaborate with software and data teams, optimize inference workflows, and contribute to scalable ML deployments while adhering to best practices in model deployment and API integration.