Senior Engineer

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Job Area:

General Summary:

Qualcomm is looking for an experienced software QA to work within an existing team to add firmware support for machine learning Edge and Datacenter use cases. The development target is Qualcomm’s next generation high-performance inference accelerator.

Candidate should have a background in embedded software development and AI inferencing such as:

• Chipset Power Blocks
• Low-Speed Peripheral Interfaces (I2C/SPI/UART)
• PCIe and Efficient Data Movement using DMA
• Hardware/Software Bring-up and System Validation
• Development Integration and Functional Testing (DIFT)
• Test Automation Frameworks and CI Infrastructure
• Software Quality and Regression Testing
• ML Inference Software Stack (vLLM, Runtime, Compiler)
• Open Source AI Models and Framework Integration

Critical Skills and Aptitude

• Understanding of the ML software ecosystem and QA approaches/frameworks
• Strong fundamentals of Deep learning, transformer architecture, industry-grade LLM serving KPIs
• Responsible for development of test strategies and ML test harnesses for AI Inference Accelerators
• Ability to interact with firmware and app software stacks stakeholders and define workflows.
• Strong experience in Python and Shell scripting for test automation and infrastructure development.
• Experience with C/C++ software development, debugging, and testing on embedded platforms.
• Experience developing automated test frameworks and Development Integration Testing (DIFT) solutions.
• Experience with CI/CD pipelines, Jenkins, Git/Gerrit, and build automation.
• Strong understanding of SoC architecture, memory hierarchy, interrupts, power management, and multi-threaded programming.
• Experience validating hardware/software interfaces including PCIe, DMA, memory, and peripheral subsystems.
• Experience with software quality metrics, regression testing, and release qualification.
• Familiarity with AI inference runtimes such as vLLM and accelerator software stacks.
• Familiarity with compiler technologies, model onboarding, optimization, and deployment workflows.
• Experience working with open-source AI/ML models and frameworks such as Llama, DeepSeek, Qwen, PyTorch, Hugging Face, or similar.
• Excellent communication skills and ability to work across global cross-functional teams.

The Ideal Candidate Will Have/Demonstrate the Following

• Familiarity with high-speed interfaces such as PCIe and LPDDR.
• Familiarity with ECC, PCIe AER, RAS, and reliability validation.
• Experience with end-to-end system integration, feature validation, and Go/No-Go quality assessments.
• Experience with scalable automation frameworks, CI/CD systems, and continuous testing methodologies.
• Experience onboarding, validating, and optimizing open-source AI models on accelerator platforms.
• Experience working across firmware, runtime, compiler, and inference software stacks.
• Demonstrated technical leadership in software quality, validation, automation, and release readiness.
• Experience mentoring engineers and driving best practices across multiple teams.

Minimum Qualifications:

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Test Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field.

• 1+ year of work or academic experience with Software Test or System Test, developing and automating test plans and/or tools (e.g., Source Code Control Systems, Continuous Integration Tools, and Bug Tracking Tools).

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