Engineer, Senior

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Test Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Test Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 1+ year of work or academic experience with Software Test or System Test, developing and automating test plans and/or tools (e.g., Source Code Control Systems, Continuous Integration Tools, and Bug Tracking Tools). You will join the CR&D software team focused on definition and implementation of the overall testing strategy for a new machine learning program. This will include defining test for software/firmware features, enable automated executing and reporting, analysis of bugs and system level testing using popular ML frameworks such as PyTorch, Caffe2, TensorFlow and others. You will work closely with development and architecture team to understand accelerator features and define test plans and solutions needed to deliver production grade software/firmware to the end customer. The successful applicant should have a diverse skill set and a strong background in testing and automation strategies. Proficiency with scripting languages— Python, Shell Scripting and OOP concepts. Well-versed with firmware (RTOS) and system-level (Linux) in SOC and/or Server solutions Experience in working with Linux Operating system & C++ Programming Language Experience in bringing up embedded platforms for customers and internal engg releases Experience with test-driven development solutions like GoogleTest Experience working in AI hardware accelerators, platform software testing is a plus Experience defining tests plans/strategy and test automation solutions Strong debugging and analysis skills, for root causing complex issues Willingness to work in a high-caliber mixed software/firmware development team Understanding of machine learning concepts and neural network architectures Experience with Lauterbach/T32 & its programming language Practice Understanding of key metrics needed for qualifying platform stability for customers Experience working on LLMs, AI Inference platforms is a plus 3-5 years' experience in embedded platform test and design Master's or bachelor's in computer science or Electronics & Communication (or equivalent)