Principle Engineer/Manager - On Device Learning SW
Job Description
- Experience with Training frameworks and training process (e.g., LORA fine-tuning).
- Experience in leading teams of ML engineers.
- Knowledge on deep learning and frameworks PyTorch.
- Knowledge in Android programming.
- Optimization of algebraic operations in algorithms for HW cores (GPU, NPU, etc.).
- Knowledge in neural network model quantization.
- Experience on Qualcomm QNN SDK.
- 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 + 7 years, or PhD + 6 years).
- Drive & Develop full system design & proof of concept for on device learning on Qualcomm devices.
- Development of end-2-end embedded AI software to run neural network models on Qualcomm leading edge hardware with optimal resource.
- Design and enhance the implementation of ML/AI SW stack, kernels, and runtime software to improve performance and power efficiency.
- Collaborating with AI Processor Software & Hardware team (GPU, NPU, etc..), and high quality implementation of new ML operators/layers to optimal utilizing new capabilities in next-gen AI processor.
- Development of debugging/profiling tools for rapid prototyping & deployment of new use cases.
- World-class health benefit option providing world-class coverage to employees and their eligible dependents.
- Programs designed to help employees build and prepare for a financially secure future.
- Self and family resources to help build emotional/mental strength and resilience, as well as define purpose.
- Wellbeing programs and resources offering support to help employees Live+Well and Work+Well.
- Continuous learning and development programs.
- Tuition reimbursement.
- Mentorships.
Job Posting Date
2025-09-18
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General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, compute, auto, and IOT products through machine learning hardware and software.
Artificial Intelligence is changing the world for the benefit of human beings and societies. QUALCOMM, as the world's leading mobile computing platform provider, is committed to enable the wide deployment of intelligent solutions on all possible devices – like smart phones, autonomous vehicles, laptops, robotics, IOT devices and so on. Qualcomm is creating building blocks for the intelligent edge.
We are part of Qualcomm AI Research. In this role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software developers, work with popular neural network frameworks, and understand the architecture of Qualcomm’s SOC compute and ML HW accelerators. You will architect, design, develop & test software for machine learning tools and frameworks for proof-of-concept of efficiency on all edge devices. The successful applicant should have a strong software background, and passion to work on neural network frameworks/libraries. Prior experience developing AI software toolkits would be a big plus
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.
Responsibility:
- Drive & Develop full system design & proof of concept for on device learning on Qualcomm devices.
- Development of end-2-end embedded AI software to run neural network models on Qualcomm leading edge hardware with optimal resource
- Design and enhance the implementation of ML/AI SW stack, kernels, and runtime software to improve performance and power efficiency
- Collaborating with AI Processor Software & Hardware team (GPU, NPU, etc..), and high quality implementation of new ML operators/layers to optimal utilizing new capabilities in next-gen AI processor
- Development of debugging/profiling tools for rapid prototyping & deployment of new use cases
Preferred Skills and Experience:
- Related field at least 3 years of work experience.
- Experience with Training frameworks and training process. Eg, LORA fine-tuning.
- Experience in leading teams of ML engineers
- Knowledge on deep learning and frameworks PyTorch
- Excellent programming capability with C/C++ and Python
- Strong software design, development, and debugging skills
- Knowledge in Android programming is plus
- Optimization of algebraic operations in algorithms for HW cores (GPU, NPU, etc..) is a plus
- Knowledge in neural network model quantization is a big plus
- Experience on Qualcomm QNN SDK is a big plus
