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

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.

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.

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