About the Company
Qualcomm’s Computer Vision Systems team delivers Vision IP solutions for Snapdragon processors across mobile, automotive, and VR/AR platforms. This team specializes in computer vision algorithms, architecture design for CV accelerators, and hardware modeling, with a focus on power and performance optimization.
About the Role
The team is seeking a Vision API Solution Architect with proven expertise and hands-on experience in developing and commercializing Computer Vision applications, libraries, and SDKs. Knowledge of CV hardware accelerators is a plus, though not required.
Key Responsibilities:
-
Lead the design and implementation of Computer Vision APIs as part of the Snapdragon Vision API Suite.
-
Guide development teams in creating and deploying Computer Vision APIs and related applications.
-
Produce detailed technical documentation, diagrams, and examples to highlight the benefits of the APIs.
-
Ensure project timelines are met and address any risks to project schedules.
-
Collaborate with systems, software, hardware, and product teams during the design, validation, and commercialization of APIs.
-
Work within a fast-paced, collaborative environment with globally distributed teams.
Required Qualifications:
-
Bachelor’s degree in Computer Science, Electrical Engineering, or a related field.
-
3-5 years of hands-on experience in computer vision applications or library development.
-
Strong understanding of computer vision concepts, algorithms, and deep-learning-based pipelines.
-
Proficiency in API design principles, creating scalable and user-friendly APIs.
-
Expertise in C/C++/Python, with the ability to build and evaluate API prototypes.
Preferred Qualifications:
-
Familiarity with computer vision libraries such as OpenCV, TensorFlow, and PyTorch.
-
Knowledge of embedded systems and hardware CV accelerators.
-
Experience in writing comprehensive technical documentation.
-
Familiarity with commercial software development and SDLC processes.
Minimum Qualifications:
-
Bachelor’s degree in Computer Science, Electrical Engineering, or related field with 4+ years of relevant experience, or
-
Master’s degree with 3+ years of relevant experience, or
-
PhD with 2+ years of relevant experience.