Edge AI & Computer Vision Engineer

Qualcomm; San Diego (CA); On-site; USD 130,000 - 194,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a machine learning R&D engineer for its Computer Vision Systems team.

You will develop edge AI algorithms for vision tasks across mobile, automotive, XR, and robotics platforms, translating research into production deployments. The role combines computer vision, ML model development, and hardware/software optimization on heterogeneous SoCs, with opportunities to publish, contribute IP, and collaborate with cross‑functional teams.

Qualifications

• Bachelor's degree in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of related work experience.
• Master's degree in Computer or Electrical Engineering, Computer Science, or related field and 1+ year of related work experience.
• PhD in Computer or Electrical Engineering, Computer Science, or related field.

Responsibilities

• Research, design, and implement advanced video processing and computer vision algorithms (depth estimation, optical flow, 3D reconstruction).
• Develop optimized model architectures and training strategies for edge deployment on heterogenous SoCs.
• Profile and optimize algorithms for memory, compute, power, and bandwidth constraints across mobile platforms.
• Collaborate with hardware, software, systems, and product teams to meet customer requirements, and document designs and results.

Skills

Python

C/C++

Deep learning

Computer vision

Edge deployment

Education

Bachelor's degree in EE/CS

Master's degree in EE/CS

PhD in EE/CS

Tools

PyTorch

TensorFlow

ONNX

OpenCV

C/C++

Job description

Qualcomm Technologies, Inc. is seeking a machine learning R&D engineer for its Computer Vision Systems team.

You will develop edge AI algorithms for vision tasks across mobile, automotive, XR, and robotics platforms, translating research into production deployments. The role combines computer vision, ML model development, and hardware/software optimization on heterogeneous SoCs, with opportunities to publish, contribute IP, and collaborate with cross‑functional teams.