Senior Staff ML Compiler and Performance Engineer

We are partnered with a global leader in the semiconductor industry assisting in the search for a Senior-Staff level compiler optimization engineer to join their growing AI/ML R&D team.

General Summary:

Today more intelligence is moving to end devices and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile We envision making AI ubiquitousexpanding beyond mobile and powering other end devices machines vehicles and things.

We are inventing developing and commercializing power-efficient on-device AI edge cloud AI and 5G to make this a reality.

Job Purpose & Responsibilities

As a member of the ML Systems Team you will participate in two activities:

• Development and evolution of ML/AI compilers (production and exploratory versions) for efficient mappings of ML/AI algorithms on existing and future HW
• Analysis of ML/AI algorithms and workloads to drive future features in Qualcomms ML HW/SW offerings

Key Responsibilities:

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

Minimum Qualifications:

Requirements:

• Demonstrated ability to learn think and adapt in fast-changing environments
• 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
• Knowledge of network model formats/platforms (eg. Pytorch Tensorflow ONNX) is an asset.
• On-silicon debug skills of high-performance compute algorithms Knowledge of algorithms and data structures
• Knowledge of software development processes (revision control CD/CI etc.) Familiarity with tools such as git Jenkins Docker clang/MSVC
• Knowledge of computer architecture digital circuits and event-driven transactional models/simulators