Q

Qualcomm

Designs mobile chips and licenses wireless patents

Computer Vision System Engineer - Video Systems, HW Architecture

Hardware Systems IntegrationConfirmed live in the last 24 hours
Full-timeSan Diego, CA, USAIn-person

About the Job

Requirements

  • A Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field and at least 2 years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience; or a Master's degree in those fields and at least 1 year of related work experience; or a PhD in those fields.
  • Strong expertise in hardware-aware algorithm design, deep learning engine architecture, system architecture, hardware/software co-design, and accelerator development for mobile computer vision and artificial intelligence workloads.
  • Deep knowledge of computer vision and neural network algorithms, and practical experience translating them into power-efficient, real-time implementations on heterogeneous mobile platforms.
  • Strong understanding of mobile computer vision applications, including object detection and tracking, segmentation, scene understanding, image enhancement and computational photography, motion estimation, and neural network-based vision systems.
  • Expertise in system architecture and hardware/software partitioning for computer vision and artificial intelligence workloads.
  • Strong understanding of deep learning accelerator architectures, including tensor processing, optimization, compute, and neural network bottlenecks.
  • Experience defining real-time hardware architectures for computer vision and deep learning workloads.
  • Experience evaluating throughput, latency, power, memory bandwidth, and silicon area trade-offs.
  • Strong programming skills in C/C++ and Python, with hands-on experience in algorithm prototyping and performance analysis.

Responsibilities

  • Study state-of-the-art computer vision and deep learning models and define efficient mappings onto mobile AI accelerators and heterogeneous compute platforms.
  • Drive architecture development for hardware-aware deep learning engines, including support for emerging neural network operators, dataflows, tensor processing pipelines, quantization techniques, and memory hierarchies.
  • Analyze neural network workloads and identify architectural enhancements required to improve performance, power efficiency, memory bandwidth utilization, and silicon area.
  • Define hardware/software partitioning strategies across CPUs, GPUs, DSPs, NPUs, and dedicated accelerators.
  • Develop workload characterization methodologies and performance models for computer vision and AI applications.
  • Collaborate with hardware architects and designers to define next-generation AI engine features and capabilities based on evolving computer vision workloads.
  • Drive top-down architecture exploration from algorithm requirements through hardware implementation, including performance, power, thermal, and area projections.

Desired Qualifications

  • Multiple years of experience developing mobile computer vision and AI systems.
  • Deep knowledge of modern neural network architectures, including CNNs, Transformers, Vision Transformers (ViTs), multi-modal perception systems, and hardware-aware model optimization techniques.
  • Experience architecting and optimizing deep learning engines (DLEs) or AI accelerators for computer vision workloads.

About the Company

Qualcomm

Designs mobile chips and licenses wireless patents

Qualcomm designs the Snapdragon processors and modems inside many Android phones, and it licenses its wireless patents to device makers around the world. It helped commercialize CDMA, the cellular technology behind 3G networks, and its patents cover core parts of the 4G and 5G standards that phones use to connect. The company does not run its own chip factories; contract foundries make its chips, which it sells to makers of phones, PCs, cars, and connected devices. Device makers also pay Qualcomm royalties for using its patented technology, which forms a second business alongside chip sales. Qualcomm was founded in 1985 and is based in San Diego, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Diego, CA
Founded
1985

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