Posted:1 month ago| Platform:
Hybrid
Full Time
Job Description In this role, you'll be programming in Python, C++ and C to create the core software that powers advanced computer vision and modeling applications. These tools use complex math to interpret and generate visual data, like images or 3D models. Youll get to work with the latest research in fields like artificial intelligence, computer vision (helping users see and understand images), and computer graphics (generating images or animations). The ideal candidate Should have a proven track record of success in Deep learning projects and handling team of product based on AI , a strong technical background, and excellent communication skills. Responsibilities include, but not limited to: Implement, in Python, core deep-learning/computer vision and (inverse-) procedural modeling algorithms, with varying levels of oversight. These algorithms rely on mathematical techniques from linear, algebra, probability, and geometry. Apply cutting-edge research in machine learning, computer vision, and computer graphics. Work closely with leadership to understand high-level product vision and customer requirements. Utilize Git for effective source code management. Deploy and test your code on large scale geospatial datasets .This requires you to interact with remote machines via a Unix shell. Qualifications degree in Computer Science, Engineering, Mathematics, or a related field 6+ years of relevant industry experience in a fast paced, high growth tech environment. Proficiency in Python , C++ and Embedded device programing Experience training artificial neural networks or adjacent experience (e.g. gradient descent / nonlinear optimization / classical machine-learning) Team-oriented and collaborative approach with a demonstrated aptitude, enthusiasm and willingness to learn new methods, tools, practices and skills Strong communication skills with the ability to translate complex technical concepts into clear, accessible language for non-technical stakeholders. Hands-on experience with TensorFlow and Keras (or similar frameworks) in developing, training, and deploying deep learning models.
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