Company:
Qualcomm Semiconductor Limited
Job Area:
Engineering Group, Engineering Group > Hardware Applications Engineering
General Summary:
Join Qualcomm’s AI Appliance IoT Edge Team to architect, design, and deliver next-generation edge AI appliances powered by Qualcomm inference cards (AI100, AI200, AI250).
You will work closely with ODMs/OEMs to create robust, scalable, and efficient hardware solutions for industrial, enterprise, and edge deployments, with a strong focus on thermal, power, and mechanical integration.
AI Inference Card Integration
- Lead the integration of Qualcomm AI inference cards (AI100, AI200, AI250) into appliance platforms, ensuring optimal electrical, thermal, and mechanical performance.
- Define and implement high-speed interconnects (PCIe Gen5/6, Ethernet, DDR5/LPDDR5x) between inference cards and host systems.
- Collaborate with ODMs/OEMs to design custom carrier boards, backplanes, and expansion modules for AI inference accelerators.
- Develop and validate power delivery architectures to support high-performance AI workloads, including VRMs, PMICs, and redundant power supplies.
- Ensure robust cooling solutions for inference cards, including heat sinks, vapor chambers, fans, and liquid cooling, tailored for edge environments.
- Support firmware and software integration for card management, BMC, and remote monitoring.
On-Prem Edge Deployment Scenarios
- Architect appliance solutions for on-prem edge deployments in industrial, retail, smart city, and enterprise environments.
- Design for ruggedization, wide temperature range, vibration, dust, and humidity resistance to meet edge deployment requirements.
- Ensure compliance with local and global regulatory standards (CE, FCC, UL, RoHS) for edge appliances.
- Optimize mechanical design for compact form factors, wall/rack mounting, and easy field servicing.
- Collaborate with system integrators and customers to tailor appliance designs for specific edge use cases (e.g., real-time video analytics, industrial automation, smart retail).
- Support remote and on-site deployment, validation, and troubleshooting of edge AI appliances.
General Hardware Engineering
- Lead schematic capture, PCB layout, and component selection for high-density, high-speed boards.
- Drive cross-functional collaboration with mechanical, thermal, SI, validation, manufacturing, and firmware/software teams.
- Conduct design reviews, thermal simulations, and compliance testing.
- Travel to ODM/OEM and customer sites as needed for deployment, validation, and troubleshooting.
Required Experience
- 8+ years in hardware/system design, with significant experience in appliance or edge device development for industrial or enterprise IoT.
- Proven track record integrating AI inference accelerators into appliance platforms.
- Deep expertise in thermal management, power delivery, and mechanical integration for edge appliances.
- Experience with high-layer count PCB design, high-speed serial interfaces, and complex board topologies.
- Familiarity with compliance testing, regulatory standards, and environmental requirements for edge hardware.
- Hands-on experience with schematic capture and PCB layout tools (Cadence Allegro, Mentor Expedition), and lab equipment (oscilloscopes, logic analyzers, JTAG).
- Strong understanding of firmware/software integration, especially BMC and x86 architectures.
Minimum Qualifications
- Bachelor’s degree in Electrical/Electronic Engineering, Computer Engineering, or related field.
- 12+ years of hardware engineering experience, including appliance-level design and ODM/OEM collaboration.
Preferred Qualifications
- Master’s degree in Electrical/Electronic Engineering, Computer Engineering, or related field.
- Experience designing edge appliances for AI inference accelerators
- Expertise in ruggedized, industrial, or outdoor appliance design.
- Experience with regulatory and compliance testing for global edge deployments.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Applications Engineering, Software Development experience, or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Applications Engineering, Software Development experience, or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Applications Engineering, Software Development experience, or related work experience.
• 3+ years of experience with Programming Language such as C, C++, Java, Python, etc.
• 3+ years of experience with debugging techniques.
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