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Looking for An Exciting Growth Opportunity? Thinci is the place! We are looking for high-energy, passionate technical professionals to join our fast-growing company. Summary Thinci is a pioneering AI silicon and platform solutions company delivering the next generation of efficient computing with innovations in architecture, software and systems. Thinci products enable the unique computational requirements of the exploding AI solutions & impact markets, which are projected to rise rapidly to $3T in revenue by 2024. Now at commercialization stage, Thinci is shipping product, generating revenue and growing to meet demand with customers across a range of growth market sectors.We are actively looking for enthusiastic and talented upper-mid-level to senior Machine Learning Engineer to join our team on an intelligent Machine Learning developer tools software project. This role requires experience designing, building and training Generative Adversarial Networks for purpose of generating content. Candidate should have a history of working within an Agile product delivery team, strong understanding and practice of coding standards, knowledge of the intricacies of common ML frameworks and languages, cloud-based data management products, and excellent problem-solving skills. Title: Machine Learning Engineer Reporting: VP Research and Product Development Responsibilities Lead design and development of engineering tools for non-coding ML users Write, test, and document robust hands-on code with C/C++ and Python Collaborate closely with a team of AI experts to solve problems in computer vision, visualization of ML results, and user – ML system interaction Stay informed about developments in AI and utilize state-of-the-art technology as it emerges Education and Experience Education: M.S./Ph.D. in relevant field or equivalent experience Experience: 1+ years of solid experience designing, training, and implementing autoencoders and/or GANs Strong programming skills in Python and C++ Use of good programming practices including writing, testing, and documenting robust and maintainable code In-depth knowledge of common deep learning frameworks such as PyTorch, TensorFlow, or Keras Solid understanding of computer vision fundamentals Proficiency with computer vision toolkits such as OpenVX is a plus Broad understanding of Machine Learning across multiple domains, algorithms and applications Staying current with research on GANs and the latest developments in the AI area, broadly taken Proven experience solving problems using deep neural networks, preferably in the field of computer vision Projects demonstrating your skill set, including published papers, starred GitHub repositories, and/or Kaggle scores Experience with Agile software development methodology is a plus