Technical Staff Engineer - Design
Microchip Technology Inc. · Chandler, AZ · 1 wk ago
On-siteEngineeringFull-time
Job Description
Microchip Technology's MCU Business Unit is at the forefront of Edge AI innovation, delivering production-ready, full-stack solutions that bring intelligent real-time decision-making to industrial, automotive, data center, and consumer IoT networks. We are seeking an experienced Technical Staff Engineer to drive chiplet-based architecture definition and advanced-node product research for our next-generation microcontrollers. This senior-level role will work closely with the other business units and cross-functional teams to align chiplet definitions with platform, technology, and product requirements.
Key Responsibilities
- Define and drive chiplet-based architectures for edge AI microcontroller platforms, including specification of chiplet boundaries, interfaces, power domains, and integration strategies that optimize for cost, performance, and manufacturability.
- Collaborate closely with the analog business unit to align on chiplet definitions, die-to-die interface specifications, packaging requirements, and integration roadmaps ensuring consistency across platform and product lines.
- Perform comprehensive architectural trade-off analysis to optimize power, performance, area, and cost for MCU-class products, utilizing modeling, simulation, and benchmarking to validate design decisions against product requirements.
- Conduct advanced-node product research, feasibility studies, and technology definition activities including evaluation of process capabilities, design rule impacts, and technology-specific optimization opportunities for edge AI workloads.
- Develop and optimize end-to-end advanced-node design flows for high-volume MCU products, working with EDA vendors and internal CAD teams to establish robust methodologies for synthesis, placement, routing, timing closure, and verification.
- Work cross-functionally with AI accelerator, CPU core, memory subsystem, embedded software, advanced packaging, and manufacturing teams to ensure holistic system optimization and successful product delivery.
- Support architecture reviews, technical alignment meetings, and product definition milestones by preparing technical presentations, documentation, and recommendations for executive and engineering audiences.
- Provide technical leadership and mentorship to junior engineers within the MCU and Edge AI engineering teams, fostering a culture of innovation, technical excellence, and continuous learning.
Requirements/Qualifications
- Required Qualifications:
- Bachelor's Degree in Electrical or Computer Engineering (or similar degree), Masters Degree preferred.
- Minimum of 10+ years of relevant experience with Verilog/SystemVerilog and/or VHDL.
- Strong knowledge of chiplet-based or modular architectures and system-level integration, including understanding of die-to-die interconnect standards and 2.5D integration techniques.
- Hands-on experience with advanced-node FinFET technology nodes and associated design flows.
- Possess excellent analytical and problem-solving skills.
- Excellent communication and documentation skills (verbal and written).
- Proficiency with EDA tools for architecture exploration, RTL design, synthesis, and physical implementation.
- Experience with hardware description languages (Verilog, SystemVerilog, VHDL) and scripting languages (Python, Tcl, Perl) for design automation.
- Preferred Qualifications:
- Experience working with cross-business-unit teams on shared IP, chiplet definitions, or platform architectures.
- Background in edge AI acceleration, digital signal processors, or embedded machine learning inference engines.
- Proven track record in high-volume, cost-sensitive MCU product development from architecture definition through production.
- Familiarity with silicon bring-up, validation, debug, and production lifecycle support activities.
- Knowledge of UCIe (Universal Chiplet Interconnect Express) or other chiplet interface standards and their implementation.
- Experience with advanced nodes (e.g., 7nm-class and beyond) and roadmap planning.
Physical Attributes
- Hearing: 90%
- Sight: 90%
- Talking: 10%
- Works Alone: 90%
- Works Around Others: 10%