About The Company

Qualcomm is a global leader in the semiconductor and telecommunications equipment industry, renowned for its innovative solutions in wireless technology. With a focus on advancing mobile and connected device capabilities, Qualcomm develops and supplies integrated circuits, software, and services that power a wide range of devices and applications worldwide. The company's commitment to research and development has established it as a pioneer in 5G, AI, and IoT technologies, fostering a culture of innovation that drives the future of connectivity.

About The Role

We are seeking a skilled Machine Learning Software Engineer with embedded experience to join our dynamic team at Qualcomm. In this role, you will be instrumental in developing and delivering cutting-edge embedded AI solutions tailored for infotainment systems and Advanced Driver Assistance Systems (ADAS)/Autonomous Driving applications. Your expertise will contribute to creating efficient, high-performance inference engines that operate seamlessly on embedded hardware platforms. This position offers an exciting opportunity to work at the forefront of automotive and embedded AI technology, collaborating with cross-functional teams to co-design and optimize AI workloads for real-world deployment.

Qualifications

The ideal candidate will possess a strong educational background in Computer Science, Engineering, or related fields, complemented by hands-on experience in embedded systems and performance optimization. A minimum of a Bachelor's degree with at least 2 years of relevant work experience, or a Master's degree with 1 year of experience, is required. Candidates holding a Ph.D. in a related discipline are also encouraged to apply. Proficiency in C++ programming, embedded system design, and familiarity with Linux/Android/QNX development environments are essential. Knowledge of computer architecture, AI accelerators, DSPs, and machine learning concepts will be advantageous. Candidates should have a solid understanding of model deployment frameworks such as Onnx, TensorFlow, or PyTorch.

Responsibilities

Design and implement core components of the machine learning runtime framework optimized for inference on embedded systems. Collaborate with compiler, hardware, and model teams to co-design efficient execution paths for AI workloads, ensuring optimal performance and resource utilization. Develop and maintain high-quality C++ code for runtime kernels and system-level integration, supporting scalable and maintainable solutions. Create tools for performance profiling and debugging, focusing on quantized model accuracy and runtime behavior analysis. Utilize profiling tools and hardware counters to analyze and enhance runtime performance, identifying bottlenecks and optimization opportunities. Support the deployment of machine learning models from popular frameworks such as Onnx, TensorFlow, and PyTorch onto Qualcomm's inference stack, ensuring seamless integration and operation. Drive innovation by challenging existing processes and implementing best practices to develop industry-leading embedded AI solutions.

Benefits

Qualcomm offers a competitive compensation package, with a pay range of $114,400 to $164,400 annually, complemented by a discretionary bonus program and RSU grants. Employees benefit from comprehensive health insurance plans, retirement savings options, and various wellness programs. The company fosters an inclusive and collaborative work environment, supporting professional development through training and growth opportunities. Qualcomm also emphasizes work-life balance, providing flexible work arrangements and employee assistance programs to promote overall well-being.

Equal Opportunity & Disability Accommodations

Qualcomm is an equal opportunity employer committed to fostering diversity and inclusion in the workplace. We welcome applications from individuals of all backgrounds and experiences. If you require accommodations during the application or hiring process due to a disability, Qualcomm is dedicated to providing accessible procedures and support. Please contact our HR team to request reasonable accommodations.