Staff Engineer - AI Software Enigneer

Excellent C++/Python programming skills. Strong software development skills (e.g., data structure and algorithm design, object-oriented or other software design paradigms, software debugging and testing). Experience with agile software development practices, git-based SCM and Linux development environment. Proven track record of leading teams and delivering software solutions. Strong system-level thinking skills. Strong communication skills (verbal, presentation, written) and ability to collaborate with globally distributed, cross-functional stakeholders. Experience in on-device software development or heterogeneous computing platforms (CPU, GPU, NPU, DSP, ASIC HW etc). Experience with low-level interactions between operating systems (Linux, Android, QNX, Windows) and hardware. Foundational knowledge of Machine Learning and Deep Learning. Experience in AI inference on HW accelerators, with a strong focus on key KPIs such as performance, accuracy, and end-to-end inference metrics. Exposure to AI frameworks (e.g., PyTorch/TensorFlow/ONNX). Experience in embedded / systems software on SoCs (Linux/Android/QNX). Experience with AI software and model deployment for automotive platforms. Bachelor's/Master's in engineering, Computer Science, or related field. 9 to 13 years of industry experience in software engineering with solution-oriented mindset. Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc. Own project-level responsibilities, working with cross-site stakeholders to meet project milestones. Define the technical direction and architecture for a domain or workstream. Drive cross-functional alignment and decision-making. Drive stability, functional, and quality issue resolution, and refactoring/modularization and validation efforts. Drive in design and code reviews. Apply best software engineering practices to deliver clean, maintainable, and testable code. Mentor team members