Senior Computer Vision Engineer en Niuro

At Niuro, we connect elite tech teams with innovative projects in collaboration with leading U.S. companies. Our mission emphasizes simplifying global talent acquisition through efficient and high-quality solutions. We empower our teams by providing opportunities for continuous professional growth, ensuring success in technologically challenging projects. As such, we handle all administrative aspects including hiring and payments, allowing our professionals to focus on achieving outstanding results in their respective fields.

• Model Development & Optimization: Enhance accuracy and speed of YOLO (or similar models) through advanced CNN architectures and optimization techniques.
• Dataset Management & Augmentation: Expand and refine datasets, utilizing data augmentation techniques to enhance model robustness.
• Model Training & Evaluation: Train and validate models against key metrics (precision, recall, mAP) to ensure reliable performance in real-world scenarios.
• Deployment on Embedded Hardware: Optimize and deploy models on Jetson Orin Nano (or similar) using TensorRT for high-speed inference.
• Real-World Validation: Test models in sterilization and surgical environments, iterating and refining based on real-world performance feedback.

• Computer Vision Expertise: 5+ years in deep learning and computer vision.
• Model Development: Strong experience with YOLO, Faster R-CNN, EfficientDet, or similar architectures.
• Deep Learning Frameworks: Proficiency in PyTorch or TensorFlow for model training and optimization.
• Data Handling: Experience managing large datasets and applying data augmentation techniques.
• Performance Optimization: Knowledge of model quantization, pruning, and employing TensorRT for real-time inference.
• Embedded AI: Proven experience deploying models on NVIDIA Jetson devices.
• Evaluation & Metrics: Strong familiarity with key performance metrics including mAP, IoU, recall, and precision.
• Software Development Skills: Proficiency in Python, with experience in C++ being a plus.
• Problem-Solving & Debugging: Ability to fine-tune models based on real-world feedback.
• OpenCV Expertise: Demonstrable experience with OpenCV for advanced image processing and real-time computer vision applications.

• Experience with ONNX, OpenVINO, or similar model optimization tools.
• Familiarity with ROS (Robot Operating System) for robotics applications.
• Experience in medical imaging or AI applications within healthcare.
• Knowledge of sensor fusion technologies such as LiDAR and depth cameras.