Company:
Qualcomm Semiconductor Limited
Job Area:
Engineering Group, Engineering Group > Software Engineering
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, edge, auto, and IOT products through machine learning hardware and software.
We are looking for a Staff or Senior Staff level Engineer to work on bleeding-edge AI technology. You will architect high-performance software for AI engines, including Qualcomm AI Engine Direct (QNN), and define the strategy for deploying Large Language Models (LLM) and Vision-Language Models (CLIP) on strictly power-constrained hardware. You will collaborate with cross-functional teams (HW/SW architecture) to enhance the world of mobile, edge, and IoT products. This is a great opportunity to innovate and develop leading-edge products around best-in-class Qualcomm AIoT devices.
Responsibilities
Architectural Leadership: Lead the development of AI SW stack framework enhancements for optimal resource usage while running complex Transformer-based networks (LLM, ViT) on Qualcomm hardware.
Research to Production: Lead efforts in transitioning research (e.g., new quantization techniques, efficient CLIP encoders) into production-ready solutions, enabling real-world applications and commercial impact.’
GenAI Optimization: Drive the development of optimization algorithms for ML operators/layers specific to Generative AI (e.g., KV-cache optimization, attention acceleration) within the Qualcomm AI SW stack.
Performance Tuning: Evaluate and optimize neural networks’ runtime performance (latency, memory, power) and accuracy using tools like AIMET and QNN SDK.
Software Development: Develop software tools for profiling and debugging to support the rapid deployment of new neural networks.
Feature Enablement: Work with customer teams to enable state-of-the-art network models and new AI SW features to meet customer use-cases, and collaborate with AI hardware teams to continuously improve our AI solution.
Minimum Qualifications
Master's degree in Electrical Engineering, Computer Science, Mathematics, Physics, or a closely related field with 7+ years of relevant experience, or a PhD with 4+ years of experience.
Proficient in modern C, C++, and Python.
Deep experience in neural network deployment, quantization, and model compression (specifically for Transformers/LLMs).
Solid understanding of neural network inference frameworks for embedded systems (e.g., QNN, TFLite, NCNN, ONNX).
Preferred Qualifications
8+ years of experience in embedded Linux development or AI/ML application engineering.
Experience in video/image processing, computer vision, or multimedia algorithm development (relevant for CLIP/Vision tasks).
Hands-on experience with LLM/CLIP model pipelines, including fine-tuning, evaluation, and optimization on NPU/DSP.
Experience with Qualcomm AI Stack specifically "AI Engine Direct SDK (QNN)" and "AI Model Efficiency Toolkit (AIMET)".
Familiarity with hardware accelerators (Hexagon DSP) and embedded architectures.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
• 3+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
Applicants: Qualcomm is an equal opportunity employer. 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.com or call Qualcomm's toll-free number found here. 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. We will not respond here to requests for updates on applications or resume inquiries).
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies: Our 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. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers.