Software Engineer, AI Software Core; levels

Company

Qualcomm Technologies, Inc.

Engineering Group, Engineering Group >
Machine Learning Engineering

As a leading technology innovator, 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 an AI Software Core 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 role, you will be responsible for designing, developing, and optimizing features for the Qualcomm AI Stack within the 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. Depending on level, you may assist or lead feature development, provide guidance to junior team members, and make decisions impacting your direct area and the broader work group.

You will collaborate with cross‑functional teams to deliver robust, scalable AI software solutions, and contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

• 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.
• Lead or 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;
  Staff Engineers provide guidance to junior team members and make decisions impacting their area and the broader work group.

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
• 2+ years (Senior) / 5+ years (Staff) of general software development experience.
• Proficiency in software development using C/C++.
• Experience with development in a Linux environment.
• Strong software development skills, including data structure and algorithm design, object‑oriented or other software design paradigms, software debugging, and testing.
• Excellent communication skills (verbal, presentation, and writing).

• Master's degree in Computer Science, Computer Engineering, or Electrical Engineering.
• 1+ years (Senior) / 3+ years (Staff) of experience building embedded software applications.
• 1+ years (Senior) / 3+ years (Staff) of software development experience with Python.
• Experience in using and developing AI solutions in one or more of these frameworks:
  Tensorflow, JAX, TFLite, LiteRT, PyTorch, Execu Torch, ONNX Runtime.
• Familiarity with various generative AI model architectures such as LLMs.
• Strong understanding of hardware…