Role & responsibilities

We are seeking an experienced Embedded AI Engineer to join our team in validating PyTorch-based Large Language Models (LLMs) using CUDA SDK APIs. The successful candidate will be responsible for debugging, extending and replacing the underlying CUDA code to ensure seamless functionality on our company-specific AI processors

- Validate PyTorch-based LLMs on company-specific AI processors using CUDA SDK APIs

- Debug and troubleshoot issues related to CUDA code integration with PyTorch models

- Extend and modify CUDA code to optimize performance on company-specific AI processors

- Replace existing CUDA code with custom implementations to meet specific requirements

- Collaborate with cross-functional teams to ensure successful integration of LLMs with company-specific AI processors





- Develop and maintain validation frameworks and tools for PyTorch-based LLMs

- Analyze and optimize the performance of LLMs on company-specific AI processors

Preferred candidate profile

- Bachelor's or Master's degree in Computer Science, Electrical Engineering or related fields

- Robust experience with CUDA programming and PyTorch framework

- In-depth knowledge of deep learning models, particularly Large Language Models (LLMs)

- Proficiency in C++ and Python programming languages

- Experience with debugging and troubleshooting complex software issues

- Excellent problem-solving skills and attention to detail

- Strong communication and collaboration skills

📌 AI/ML CUDA Engineer (Bengaluru)
🏢 QFocus AI
📍 Bengaluru