- Location
- Markham, ON,CA, CA
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Education
- PhD
- Closing date
- 4 weeks ago
- Source
- Eightfold
Description
Design and develop impactful solutions to optimize GenAI model execution on-device, leveraging Hexagon DSPs for efficient inference latency and power. Lead project discussions and analysis on system and model deployment designs for GenAI models Use cross compiler toolchains for embedded systems such as Android, embedded Linux, Windows on Snapdragon and QNX Implement and optimize Machine Learning operations using modern C++17 on Hexagon DSP systems Contribute to the development of tools and GenAI workflows for chip design, model and system analysis Participate in software quality process improvements Six or more years of relevant work experience Experience with modern C++17 language features and C++ design patterns Background in mathematical algorithms using fast math libraries and vector instructions sets Practical experience with developing middleware or firmware software Experience with multitasking and multithreading driver development Experience with Hexagon DSP SDK or cross compiler toolchains for embedded systems and JIT technologies Experience with low level interactions between operating systems and hardware. Familiarity with TensorFlow, PyTorch or ONNX Experience with agile software development practices, Jira system and tools such as git Ability to collaborate and lead discussions across a globally diverse team Minimum: Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering Preferred: Master's degree in Computer Science, Computer Engineering, or Electrical Engineering 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.
