Sr Staff/Principal Devops Engineer, Machine Learning Infrastructure And Performance

Company:
Qualcomm Canada ULCJob Area:
Engineering Group, Engineering Group >
Machine Learning EngineeringGeneral 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.Purpose:
Maintain local server racks and on-site devicesMake infrastructure and processes robust, reliable, and efficientIdentify 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: LinuxDepth in: CI/CDDepth in: DockerDepth in: PythonThe 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:
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.Minimum qualifications: 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.Minimum qualifications: PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.Equal Opportunity Statement
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 View email address on ca.hrm.tc 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).
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