Deep Learning Engineer

You will be joining our team as a skilled Deep Learning Engineer with expertise in object detection and segmentation models. Your primary responsibilities will include implementing and refining object detection models such as YOLOvX, Faster R-CNN, EfficientDet, SSD, and Mask R-CNN. Additionally, you will work on real-time computer vision applications, optimize performance, annotate and prepare datasets, and collaborate on research and development projects to enhance model performance and robustness. As a Deep Learning Engineer, you will be expected to deploy models using Docker on Linux/Windows systems, with experience in edge deployment considered a plus. It will be essential for you to document code, experiments, and deployment processes while collaborating with cross-functional teams. Strong Python programming skills, knowledge of TensorFlow, PyTorch, OpenCV, and ONNX, as well as hands-on experience with Docker and familiarity with model optimization techniques like quantization and pruning are required for this role. An advantage would be your experience in edge deployments using platforms such as NVIDIA Jetson, TensorRT, and OpenVINO. Additionally, familiarity with experiment tracking tools like MLflow or Weights & Biases is a plus. The qualifications we are looking for include a Bachelors or Masters degree in Computer Science, AI, Data Science, or a related field, along with strong analytical, problem-solving, and team collaboration skills. This is a full-time position with a day shift schedule that requires in-person work at our location.,