Machine Learning Framework

• Contributing to the development and evolution of ML/AI compilers within Qualcomm
• Defining and implementing algorithms for compiling ML/AI workloads to achieve high performance and low power on Qualcomm HW
• Creating and implementing algorithms that couple PyTorch framework efficiently to Qualcomm ML/AI Compiler flows.
• Understanding trends in ML network design, through customer engagements and latest academic research, and how this affects both SW and HW design
• Exploration and analysis of performance/area/power trade-offs for future HW and SW ML algorithms
• Creation of performance-driven simulation components (using C++, Python) for analysis and design of high-performance HW/SW algorithms on future SoCs
• Pre-Silicon prediction of performance for various ML algorithms
• Running, debugging and analyzing performance simulations to suggest enhancements to Qualcomm hardware and software to tackle framework, compute and system memory-related bottlenecks

· Successful applications will work in cross-site, cross-functional teams.

Requirements:

• Demonstrated ability to learn, think and adapt in fast changing environment
• Detail-oriented with strong problem-solving, analytical and debugging skills
• Strong communication skills (written and verbal)
• Strong background in algorithm development and performance analysis is essential

The following experiences would be significant assets:

• Strong object-oriented design principles
• Strong knowledge of C++
• Strong knowledge of Python
• Experience in compiler design and development is an asset
• Knowledge of network model formats/platforms (eg. Pytorch, ONNX) is a strong asset.
• Knowledge of software development processes (revision control, CD/CI, etc.) · Familiarity with tools such as git, Jenkins, Docker, clang/MSVC
• On-silicon debug skills of high-performance compute algorithms · Knowledge of algorithms and data structures
• Knowledge of computer architecture, digital circuits and event-driven transactional models/simulators