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Embedded Software Engineer - AI Platform Solutions
Contributing to the architecture and design of the overall AI solutions platform.
• Optimizing the AI solutions developed for performance and designing them for scalability.
• Developing Bare Metal and/or Linux drivers for AI acceleration engines using Xilinx SOCs.
• Developing Heterogeneous memory Management solutions for Asynchronous Multi-processing platforms.
• Evaluating AI solutions developed by Xilinx and performing comparative analysis against other industry solutions.
• Developing debug and performance analysis tools and infrastructure for AI solution development.
• Work with different teams to identify problems and create solutions
• Delivering software solutions in line with product roadmap on time with high quality.
• Involved in cross function team interaction and engagement with various key player and stakeholders in the organization.
• Play a role in all the phases of software development, from requirement gathering, analysis, design, development, testing and final release to customers.
• Provide clear and timely communication related to status and other key aspects of the project to leadership team.
• Responsible for working with customers and internal support teams for resolving critical customer escalations on need basis.
• Work with management team on project planning activities – creating project plans/schedule, risk analysis and mitigation, etc. for the projects you are working on.
• Good understanding of software development life cycle stages - design, implementation, documentation and testing of software code implementing product features and requirements
• Willingness to learn skills, tools and methods to advance the quality, consistency, and timeliness of Xilinx software products.
• Masters 2+ years of experience in Computer Science, Computer Engineering, Electrical Engineering or related equivalent
• Experience with C/C++, Embedded systems and Linux kernel/driver development for multi-processor heterogeneous systems.
• Understanding/Experience with Linux heterogeneous memory management, multi-processor synchronization and communication.
• Knowledge of AI frameworks like Caffe, Tensor flow, Theano, MXNet, etc.
• Understanding of AI application stacks including OpenCV, OpenCL, OpenVX, etc.
• Expertise with Deep Neural network architectures like CNN, RNN.
• Knowledge of Acceleration platforms like GPU, TPU, APU, FPGAs.
• You must be capable of working in a dynamic, high pressure environment.