Collaborate in a cross-functional environment spanning hardware, software and systems. Conduct research and development in Develop and prototype agentic systems that integrate LLMs with tool use, memory, and reasoning capabilities Collaborate across software, and systems teams to optimize on-device and cloud-based AI performance Build robust Python and PyTorch-based research infrastructure and production-ready code Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. PhD in Computer Science, Engineering, Information Systems, or a related field is strongly preferred; alternatively, a Master's degree with exceptional applied experience. Minimum 2 years of hands-on experience in machine learning algorithms, systems engineering, or closely related fields, with a strong preference for candidates who have contributed to real-world product development or deployment. Demonstrated industry experience, either through internships during graduate studies or post-degree roles, with a track record of applying research to practical systems. Experience working in cross-functional teams to bring AI technologies from prototype to production is highly valued.
