Senior Computer Vision & AI Video Analytics Engineer

Jobverse.io

San Mateo (CA)

On-site

USD 150,000 - 190,000

Full time

9 days ago

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Job summary

Verkada's Computer Vision team seeks a Senior Software Engineer to advance AI/ML for intelligent video analysis. You will implement and optimize CV models, including people/vehicle detection and LPR/face recognition, using C++ and PyTorch/TensorFlow.

You will deploy edge-friendly solutions and contribute to traditional CV algorithms and training of deep networks. Ideal candidates have strong software craftsmanship, experience with large-scale video data, and collaboration across teams to deliver

Qualifications

  • Experience building computer vision / ML models for video analytics.
  • Proficient in C++ and ML frameworks (e.g., TensorFlow, PyTorch).
  • Experience deploying models to edge devices or constrained environments.

Responsibilities

  • Creating and refining algorithms for detection (people, vehicles) and other intelligent video analysis tools.
  • Implementing and deploying a binary classifier using TensorFlow for large-scale camera data.
  • Detecting unusual object addition/removal in scenes and counting frequencies.
  • Training text image embeddings and vision-language models.
  • Training license plate recognition models and implementing LPR on the edge.
  • Training facial recognition models and implementing real-time facial recognition.
  • C++ – writing clean, modular code and traditional CV algorithms.
  • Training deep learning networks using PyTorch, TensorFlow, Keras, or similar.

Skills

C++
TensorFlow
PyTorch
Deep learning
Computer Vision
Edge deployment

Tools

Keras
CUDA

Job description

Verkada's Computer Vision team seeks a Senior Software Engineer to advance AI/ML for intelligent video analysis. You will implement and optimize CV models, including people/vehicle detection and LPR/face recognition, using C++ and PyTorch/TensorFlow.

You will deploy edge-friendly solutions and contribute to traditional CV algorithms and training of deep networks. Ideal candidates have strong software craftsmanship, experience with large-scale video data, and collaboration across teams to deliver

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