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At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
Job Responsibility:
Collaborate with cross‑functional teams to design complete camera system solutions that meet customer requirements and technical constraints
Partner with customer engineering teams to support and deliver solutions to a worldwide client base
Develop deployment strategies and technical roadmaps for AI solutions in camera imaging and beyond
Define and demonstrate best practices for AI accelerated system scalability, reliability, and maintainability
Design end‑to‑end camera solutions and provide strategic guidance to internal and external architecture teams
Document system architectures, tradeoffs, and key decisions throughout the development lifecycle
Requirements:
Solid experiences in systems architecture or software engineering, with proven expertise developing and deploying AI/ML solutions in production environments
Strong understanding of AI/ML algorithms, frameworks, and deployment workflows
Experience with ONNX, ROCm, TensorFlow, and PyTorch
Proficiency in Python and C/C++
Effective communicator and team player, experienced in working across global teams, time zones, and cultural contexts
BS/MS degree in Computer Science, Electrical/Computer Engineering, or Applied Math
Nice to have:
Experience with camera low-level drivers (Windows or Linux)
Knowledge of camera tuning and optimization, camera sensor drivers and imaging pipelines
Background in computer vision applications, edge AI and embedded systems
Knowledge of real‑time processing, low‑level driver/firmware development, and system‑wide software engineering principles