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Computer Vision Engineer

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Qualcomm
Full Time position
Listed on 2026-03-07
Job specializations:
  • Engineering
    Computer Science, Embedded Software Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Company

Qualcomm Technologies, Inc.

Job Area

Engineering Group, Engineering Group >
Video Systems, HW Architecture

General Summary

Qualcomm’s Computer Vision Systems team is building the intelligence behind the world’s most advanced Snapdragon‑powered devices, from next‑generation mobile phones to autonomous vehicles, IoT, robotics, and immersive AR/VR platforms. The group’s work spans computer vision and video algorithm development, mapping these algorithms to computer vision and neural‑processing accelerator architectures, and efficient on‑device implementation.

We are seeking a Staff‑level, multidisciplinary engineer with deep expertise in computer vision and image/video processing algorithms, combined with strong hardware/software co‑optimization experience. This role is ideal for someone who thrives at the intersection of cutting‑edge computer vision algorithms, AI models, and efficient hardware/software implementation applied to real‑world problems.

You will own technical direction across projects, influence system‑level architecture, and drive solutions from research through production deployment. You will work on ideas that enhance everyday life—creating lasting video memories and playback experiences, and enabling innovative devices through advanced video and computer vision technologies. You will have significant opportunities to grow, lead, and shape the future of video and computer vision at scale.

Principal

Duties And Responsibilities
  • Leverage advanced video and computer vision engineering expertise to research, design, and implement critical video processing and computer vision algorithms, including video encoder, decoder, processing, quality enhancement, and real‑time computer vision pipelines, from concept through production deployment.
  • 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.
Minimum Qualifications
  • Bachelor’s degree in Computer or Electrical Engineering, Computer Science, or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
  • Master’s degree in Computer or Electrical Engineering, Computer Science, or related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
  • PhD in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Qualifications
  • 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, Tensor Flow, ONNX, and OpenCV.
  • Familiarity with hardware modeling, FPGA prototyping, or RTL design is a plus.
  • Strong ability to work across algorithm, software, and hardware boundaries.
  • Experience with real‑time computer vision systems or embedded AI deployment.
  • Experience using performance profiling tools and hardware simulators.
Level of Responsibility
  • Works independently with minimal supervision.
  • Provides technical leadership,…
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