Job Description

: We are seeking a highly skilled and motivated Software Engineer with expertise in Computer Vision and Machine Learning to join our fast-growing agritech organisation. As a Software Engineer, you will play a crucial role in developing cutting-edge solutions that leverage computer vision and machine learning technologies to revolutionise the agriculture industry. You will collaborate with a cross-functional team of engineers, data scientists, and domain experts to design and implement innovative software applications tailored for our agritech platform. Responsibilities Design, develop, and maintain software applications with a primary focus on computer vision and machine learning algorithms. Research and implement state-of-the-art computer vision and machine learning techniques to solve complex problems in the agriculture domain. Develop and optimise computer vision models and algorithms for object detection, classification, segmentation, and tracking in agricultural images and videos. Collaborate with data scientists and domain experts to analyse and annotate large-scale agricultural datasets for training and evaluation purposes. Build robust data pipelines to preprocess and transform agricultural data for machine learning models. Optimise and deploy computer vision and machine learning models on embedded systems or cloud platforms to enable real-time inference. Work closely with the product team to understand customer requirements and translate them into technical specifications and software solutions. Conduct thorough testing and debugging of software applications to ensure high-quality and reliable performance. Stay up-to-date with the latest advancements in computer vision, machine learning, and related technologies, and identify opportunities to incorporate them into our product offerings. Collaborate with cross-functional teams to provide technical expertise, guidance, and support throughout the software development lifecycle. Qualifications: Bachelor\'s or Master\'s degree in Computer Science or a related field. A Ph.D. in a relevant field is a plus. Solid understanding of computer vision principles and techniques such as object detection, image segmentation, and image classification. Strong knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and experience with training and fine-tuning models. Proficiency in programming languages such as Python, C++, or Java, with experience in developing software applications. Experience with deep learning frameworks and libraries (e.g., Keras, OpenCV) and proficiency in using popular machine learning tools and platforms. Familiarity with image and video processing techniques, including feature extraction, filtering, and image enhancement. Experience with cloud platforms and technologies for scalable deployment of machine learning models. Solid understanding of software development principles, software engineering best practices, and version control systems (e.g., Git). Strong problem-solving and analytical skills with a keen eye for detail and the ability to work in a fast-paced, dynamic startup environment. Excellent communication and teamwork skills, with the ability to collaborate effectively with cross-functional teams. Preferred Qualifications: Experience working on computer vision and machine learning projects in the agriculture or remote sensing domain. Knowledge of GIS (Geographic Information System) and spatial data analysis. Experience with edge computing and deploying machine learning models on resource-constrained devices. Familiarity with parallel and distributed computing frameworks (e.g., CUDA, Apache Spark) for accelerated processing. Publications or contributions to the computer vision and machine learning community, such as research papers, open-source projects, or participation in relevant conferences and workshops.

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