
AI Vision Architect
18 hours ago
We are seeking a highly skilled and experienced Computer Vision Engineer to lead the design and implementation of complex computer vision pipelines.
The ideal candidate will have 6–10 years of experience in architecting and deploying CV systems, with expertise in multi-object tracking, object detection, semi/unsupervised learning, and proficiency in Python, PyTorch/TensorFlow, Modern C++, CUDA.
- Design and implement complex CV pipelines for object detection, instance segmentation, industrial anomaly detection, and transition algorithms from Python/PyTorch to optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer.
- Own major modules from concept to deployment ensuring low latency and high reliability, drive long-term data and model strategies (synthetic data generation, validation frameworks), and mentor engineers to maintain high engineering standards.
Key Responsibilities Include:
- Architect and deploy CV systems with expertise in multi-object tracking, object detection, semi/unsupervised learning.
- Develop complex CV pipelines using Python, PyTorch/TensorFlow, Modern C++, CUDA.
- Implement optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer.
- Drive long-term data and model strategies (synthetic data generation, validation frameworks).
- Mentor engineers to maintain high engineering standards.
Required Skills & Qualifications:
- 6–10 years of experience in architecting and deploying CV systems.
- Expertise in multi-object tracking, object detection, semi/unsupervised learning.
- Proficiency in Python, PyTorch/TensorFlow, Modern C++, CUDA.
- Experience with real-time, low-latency model deployment on edge devices.
- Strong systems-level design thinking across ML lifecycles.
- Familiarity with MLOps (CI/CD for models, versioning, experiment tracking).
- Bachelor's/Master's degree in CS, EE, or related fields with strong ML and algorithmic foundations.
- (Preferred) Experience with NVIDIA DeepStream, GStreamer, LLMs/VLMs, open-source contributions.
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