Job AreaEngineering Group, Engineering Group Machine Learning Engineering General SummaryToday, 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-effective on-device AI, edge cloud AI, and 5G to make this a reality. PurposeAs a member of Qualcomm’s ML Systems Team, you will: Maintain local server racks and on-site devices Identify and remedy items impacting productivity of the development team. 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. 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; Turn project-specific tooling into supported, reusable platform components for other teams. Linux Python Linux infrastructure: Self-hosted GitHub Actions runners, systemd, remote filesystems (NFS), and resource monitoring. 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. IBM Spectrum LSF) or cloud infrastructure for horizontally scaling automation. 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. 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. PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. 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.
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. To all Staffing and Recruiting AgenciesOur 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.

📌 Sr Staff/Principal Devops Engineer, Machine Learning Infrastructure And Performance (Winnipeg)
🏢 Qualcomm
📍 Winnipeg