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3 days ago
Computer Vision Engineering Professional
About the Position:This role involves designing and implementing complex computer vision pipelines, ensuring efficient performance and high reliability. The ideal candidate will lead the development of critical modules from concept to deployment, transitioning algorithms from Python/PyTorch to optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer.
Key Responsibilities:- Develop sophisticated CV pipelines (object detection, instance segmentation, industrial anomaly detection)
- Own key modules from inception to deployment, focusing on low latency and high reliability
- Transition algorithms from Python/PyTorch to optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer
- Collaborate with cross-functional teams to refine technical strategies and roadmaps
- Drive long-term data and model strategies (synthetic data generation, validation frameworks)
- Mentor engineers and maintain high engineering standards
- 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
A challenging role in a dynamic environment, opportunities for growth and development, and a competitive compensation package.
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