EVA Systems Engineer

About This Role

An EVA Systems Engineer at Qualcomm Technologies, Inc. will build the intelligence behind advanced Snapdragon-powered devices, including mobile phones, autonomous vehicles, IoT, robotics, and AR/VR platforms. This multidisciplinary role involves computer vision, image and video algorithm development, mapping algorithms to computer vision and neural-processing accelerator architectures, and efficient on-device implementation. It suits an engineer who thrives at the intersection of cutting-edge computer vision algorithms, AI models, and efficient hardware/software implementation applied to real-world problems.

Responsibilities

• Lead system- and algorithm-level architecture definition, standard studies, and feature decomposition to drive hardware and software requirements and specifications
• Profile and optimize algorithm and model performance across memory, compute, power, and bandwidth constraints on mobile and embedded platforms
• Collaborate closely with cross-functional teams (hardware, software, systems, and product) and with customers to commercialize technologies and deliver best-in-class visual analytics experiences
• Write clear and concise technical documentation, design specifications, and feature descriptions to guide internal teams and external partners
• Contribute effectively in a fast-paced, highly collaborative environment with globally distributed, cross-functional teams
• Provide technical mentorship and guidance to engineers across experience levels and influence technical decisions beyond the immediate team

Requirements

• Bachelor's degree in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience
• OR Master's degree in Computer or Electrical Engineering, Computer Science, or related field and 1+ year of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience
• OR PhD in Computer or Electrical Engineering, Computer Science, or related field
• Strong background in computer vision and video processing algorithms
• Solid understanding of SoC architecture, including compute accelerators, memory hierarchies, and hardware/software interfaces
• Hands-on experience with modern deep learning architectures
• Strong coding skills in Python and C/C++ for production-quality development, optimization, and on-device deployment, with experience using ML/CV frameworks such as PyTorch, TensorFlow, ONNX, and OpenCV
• Strong ability to work across algorithm, software, and hardware boundaries
• Experience with real-time computer vision systems or embedded AI

Nice to have:

• Familiarity with hardware modeling, FPGA prototyping, or RTL design