Senior Staff Burn-In System Product Developer
advanced micro devices (singapore) pte ltd- Posted 23 hours ago
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Job Description
THE ROLE:
AMD is seeking an experienced and innovative Senior Member of Technical Staff to lead the architecture, development, and deployment of next-generation burn-in solutions for advanced semiconductor products, including CPUs, GPUs, AI accelerators, adaptive SoCs, and chiplet-based technologies. In this role, you will drive burn-in system architecture across hardware and software, enabling product quality, reliability, and manufacturing excellence throughout the product lifecycle. You will collaborate closely with Product Engineering, Reliability, Silicon Design, Packaging, Test Engineering, Manufacturing Operations, and external equipment partners to develop scalable, intelligent burn-in solutions that support AMD's leadership in High-Performance Computing (HPC) and Artificial Intelligence (AI). This position offers a unique opportunity to influence future burn-in technology roadmaps while applying advanced analytics and AI-driven methodologies to improve manufacturing efficiency, reliability screening effectiveness, and product quality.
THE PERSON:
The ideal candidate is a highly motivated technical leader with expertise in semiconductor burn-in, reliability engineering, and system architecture. You must possess outstanding vendor management and stakeholder leadership skills, with a proven track record of influencing suppliers, driving complex equipment development programs, managing technical escalations, and establishing long-term strategic partnerships. You must thrive in fast-paced environments and enjoy collaborating across multiple disciplines to enable next-generation computing platforms.
KEY RESPONSIBILITIES:
Burn-In System Architecture
- Define and drive burn-in system architecture for AMD packaged semiconductor products.
- Develop scalable burn-in solutions for advanced package technologies, including Chiplet-based architecture, 2.5D and 3D integration, HBM-enabled devices, etc.
- Lead development of system-level burn-in infrastructure, including Power delivery architecture, Thermal management systems, Burn-in boards and sockets, Control and monitoring systems, and Automation frameworks.
- Drive vendor management and supplier effectiveness to facilitate first time right and reliable performance of AMD's Burn-in solutions.
Reliability & Manufacturing
- Collaborate with Reliability and Product Engineering teams to develop burn-in strategies supporting product qualification and production requirements.
- Support New Product Introduction (NPI) and manufacturing ramp activities.
- Drive equipment evaluation, qualification, deployment, and continuous improvement initiatives.
- Analyze burn-in effectiveness and optimize throughput, equipment utilization, reliability coverage, and overall cost of ownership.
- Perform root cause analysis and corrective action implementation for burn-in-related hardware, system, and product issues.
AI, Analytics & Smart Manufacturing
- Utilize predictive analytics to identify equipment degradation, process drift, and potential product reliability risks.
- Build automated data pipelines and dashboards for monitoring burn-in performance and manufacturing metrics.
- Apply machine learning techniques for Anomaly detection, Failure prediction, Yield improvement, and Predictive maintenance
- Evaluate opportunities to utilize Generative AI technologies to accelerate engineering workflows, debug activities, and knowledge management.
PREFERRED EXPERIENCES:
- Semiconductor industry experience is required, Burn-In Engineering, Reliability Engineering, Product Engineering, Manufacturing Equipment Development, System Development
- Strong communication and technical leadership skills.
ACADEMIC CREDENTIALS:
- Bachelor's or Master's degree in electrical engineering or Electronics Engineering or Semiconductor Engineering or Related technical discipline
More Info
Key Skills
Chiplet-based architecture
Yield improvement
Thermal management systems
Power delivery architecture
Control and monitoring systems
2.5D and 3D integration
HBM-enabled devices
Burn-in boards and sockets
Generative AI technologies
Automated data pipelines
Burn-in system architecture
Failure prediction
Dashboards for monitoring
