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Qualcomm

Sr Staff/Principal DevOps Engineer, Machine Learning Infrastructure and Performance

Markham, ON, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 7, 2026

Original 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. New Position

Purpose:

As a member of Qualcomm’s ML Systems Team, you will:

Maintain local server racks and on-site devices
Make infrastructure and processes robust, reliable, and efficient
Identify and remedy items impacting productivity of the development team.

Responsibilities:

Operate and improve the Linux self-hosted GitHub runner fleet: capacity, scheduling, storage, monitoring, recovery, access, and incident response.
Build reliable GitHub Actions pipelines and reproducible Docker environments for builds, tests, model benchmarks, artifacts, and releases. Maintain the Git LFS-backed model zoo and its shared caches.
Own and innovate on the Python task/workflow orchestration infrastructure (Prefect-esque) to make hardware measurements traceable, repeatable, and actionable.
Steward performance-data ingestion and analysis, including the FastAPI/PostgreSQL-backed service and its clients; improve pytest integration, regression detection, reporting, triage, and release promotion.
Plan the next scale step: isolate workloads, improve cache and artifact lifecycle, and evaluate elastic/cloud or batch execution where it fits scarce devices and large models.
Turn project-specific tooling into supported, reusable platform components for other teams.

Required:

Depth in:

Linux
CI/CD
Docker
Python

The ideal candidate will be familiar with:

Linux infrastructure: Self-hosted GitHub Actions runners, systemd, remote filesystems (NFS), and resource monitoring.
CI/CD and containers: GitHub Actions, reusable workflows, Docker, and release automation. Familiarity with Jenkins is a plus.
Model and artifact management: Git LFS, shared caches, and large-model storage (ONNX models).
Python testing: pytest, pytest-xdist, integration tests, and performance reporting (with run-to-run variation).
AI performance tooling: ONNX, PyTorch, QAIRT SDK is a plus, Android device execution and profiling is a plus (adb).
Performance data: REST APIs, FastAPI, and PostgreSQL, or similar libraries/frameworks.
Future scaling: batch scheduling (ex. IBM Spectrum LSF) or cloud infrastructure for horizontally scaling automation.

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 disability-accomodations@qualcomm.com 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.

To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

If you would like more information about this role, please contact Qualcomm Careers.

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More about this job

Responsibilities

The role involves maintaining local server racks and on-site devices while building robust, reliable infrastructure for machine learning development. You will manage GitHub runner fleets, optimize CI/CD pipelines, and innovate on workflow orchestration to improve team productivity.

Requirements

Candidates must have a degree in a relevant field and at least 6 to 8 years of experience in hardware, software, or systems engineering. Strong proficiency in Linux, CI/CD, Docker, and Python is required to support machine learning performance and infrastructure.

Skills

Linux
CI/CD
Docker
Python
GitHub Actions
Systemd
NFS
Git LFS
ONNX
Pytest
FastAPI
PostgreSQL
Machine Learning Infrastructure
Performance Profiling
Automation
Cloud Infrastructure

Visa sponsorship

Not detected in the job text

Keywords

Linux
CI/CD
Docker
Python
GitHub Actions
Systemd
NFS
Git LFS
ONNX
Pytest
FastAPI
PostgreSQL
Machine Learning
Infrastructure
Automation
Performance Profiling
Cloud Infrastructure
Batch Scheduling
IBM Spectrum LSF
QAIRT SDK
Android
Adb
DevOps
Model Zoo
Workflow Orchestration
Regression Detection
Release Automation
Linux Infrastructure
Hardware Engineering
Software Engineering

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