Machine Learning Engineer, Frameworks & Performance (New Grad to Principal level)

MaC VC; Markham; On-site; CAD 110,000 - 160,000; Full time

Job summary

Qualcomm Canada ULC is seeking a senior ML systems engineer to help develop and optimize ML/AI compilers for efficient mappings on Qualcomm hardware. The role involves analyzing workloads, predicting performance, and advancing compiler flows that connect PyTorch to our ML stack.

You will work across cross-site teams on pre-silicon simulations, exploring high-performance HW/SW trade-offs and contributing to the next generation of energy-efficient AI processors.

Qualifications

• Strong background in hardware/software systems and ML workloads.
• Experience with ML/AI compilers and performance tuning.
• Ability to translate ML workloads to efficient HW/SW mappings.
• Excellent problem-solving and debugging in dynamic environments.

Responsibilities

• Develop and evolve ML/AI compilers for efficient mappings on HW.
• Analyze ML workloads to influence future ML HW/SW offerings.
• Create algorithms to optimize PyTorch integration with compiler flows.
• Experiment with performance/area/power trade-offs for next-gen SoCs.

Skills

C++

Python

Algorithms

Performance analysis

Debugging

Communication skills

Learning agility

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Engineering

PhD in CS/Engineering

Tools

Git

Jenkins

Docker

clang

PyTorch

ONNX

Job description

Company

Qualcomm Canada ULC

Job Area

Engineering Group, Engineering Group > Machine Learning Engineering

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, Qualcomm envisions making AI ubiquitous—expanding 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 Qualcomm’s 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 Qualcomm’s ML HW/SW offerings

Key Responsibilities

• 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 applicants 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, CPU, DSP and/or GPU 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

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ 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 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Applicants

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail [e-mail] or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.