Software Engineer, Core AI Software

Company:

Qualcomm Technologies, Inc.

Engineering Group, Engineering Group >
Machine Learning Engineering

Qualcomm pushes the boundaries of what's possible to enable next‑generation experiences and drive digital transformation, creating a smarter, connected future for all. As a Qualcomm AI Software Engineer, you will develop and implement cutting‑edge machine learning techniques that enable the efficient utilization of state‑of‑the‑art solutions across various technology verticals.

In this position, you will be responsible for assisting with the software design and development of the Qualcomm AI Stack features within Qualcomm AI Runtime (QAIRT) SDK, specifically Core software including Generative AI Inference Extensions (Genie). You will contribute to the efficient execution of advanced deep neural networks (DNNs), large language models (LLMs), and other modern AI architectures.

You will have the opportunity to demonstrate your passion for software design and development through your analytical, design, programming, and debugging skills.

• Develop software for the Qualcomm AI Stack SDKs, specifically QAIRT and Genie, to support the execution of the latest generative AI models on Snapdragon platforms.
• Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases.
• Debug complex issues, perform root cause analysis, and ensure high system reliability.
• Collaborate with cross‑functional teams to deliver robust, scalable AI software solutions.
• Assist in feature development and application of machine learning techniques into products and AI solutions, enabling customers to do the same.
• Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team.
• Participate in design and code reviews.
• Work independently with minimal supervision.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ 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 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• PhD in Computer Science, Engineering, Information Systems, or related field.

• Master’s degree in Computer Science, Engineering, Information Systems, or related field.
• 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, PyTorch, Keras).
• 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi‑media).
• 2+ years of experience with one or more programming languages suitable for machine learning (e.g., Python, R, C, C++).
• 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
• 2+ years experience working in a large matrixed organization.
• 1+ year of experience with low‑level interactions between operating systems (e.g., Linux, Android, QNX) and hardware.
• 1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).

• Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
• Models, architects, and develops machine learning hardware (co‑designed with machine learning software) for inference or training solutions.
• Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development.
• Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.
• Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance…