Senior Software Engineer

You will be responsible for developing a software pipeline that enables end-to-end ML Model Inference on a specific hardware accelerator, aiming to achieve maximum performance and accuracy. This will involve implementing cutting-edge deep learning layers for various model categories such as CNN, RNN, LSTM, GANs, etc using a customized inference pipeline for NN Processor. You will also work on performance optimization for inferencing the LLM Models on customized hardware, incorporating various layer types including transformer, encoder-decoder based models. It is essential to be hardware architecture aware and computation conscious to implement solutions effectively in an embedded device and maximize throughput. Additionally, you will be involved in developing tools and applications by producing clean and efficient code, identifying, prioritizing, and executing tasks based on requirements, and collaborating with the team to brainstorm and create new products. Mentoring fresh joiners and fostering team culture will also be part of your responsibilities. The ideal candidate should hold a BE/BTech/MS/MTech degree in Computer Science Engineering with a minimum of 4 years of experience. Strong programming skills in C/C++ and proven experience as a Senior Software Engineer are required. Experience in implementing kernel intrinsics for Machine Learning or Computer Vision algorithms with a focus on optimization is essential. Extensive experience in software development, project management, strong analytical and problem-solving skills, and adaptability to execute complex tasks under tight schedules and dynamic conditions are also necessary. Familiarity with various operating systems (Linux, Mac OS, Windows), the ability to work independently, manage a team, excellent organizational and leadership skills, and working knowledge of Deep Learning frameworks (such as ONNX, TensorFlow, PyTorch, or any Hardware Accelerator Software Pipeline Experience) are must-have qualifications. In addition to the must-have requirements, experience in managing a team size of 4 or more, working in an Agile Environment, and using automated testing frameworks are considered nice-to-have qualifications.,