Senior Printed Circuit Board Design Engineer

Senior Printed Circuit Board Design Engineer About Omnidya Omnidya is a leading insurtech company revolutionizing the insurance industry through innovative technology solutions. We leverage cutting-edge AI, computer vision, and hardware/software integrations to transform insurance processes, risk assessment, and customer experiences. Role Summary We are seeking a highly skilled Senior AI Hardware Engineer with 6-10 years of specialized experience in PCB design for AI computing systems. This role focuses on designing, developing, and optimizing custom circuit boards that integrate GPUs, NPUs, and other AI accelerators for next-generation AI applications. The ideal candidate will have deep expertise in high-performance computing hardware, thermal management for AI workloads, and signal integrity optimization for AI processing systems. This position involves full-cycle AI hardware development from concept to production, working with cutting-edge AI accelerators, high-speed interfaces, and power delivery systems optimized for machine learning workloads. You will collaborate with AI software teams, system architects, and manufacturing partners to deliver robust, scalable AI hardware solutions. Key Responsibilities AI Hardware Design & Development • Lead the design and development of custom PCBs for AI computing applications, including GPU and NPU integration boards • Design high-performance AI accelerator cards with focus on NXP and ARM GPU integration • Develop NPU integration solutions for edge AI applications using Intel Neural Compute Stick, Google Coral, and similar platforms • Create multi-GPU interconnect solutions using NVLink, PCIe Gen4/5, and CXL technologies • Design AI inference accelerator modules for edge computing and embedded AI applications Advanced PCB Design & Signal Integrity • Execute complex PCB layouts for high-speed AI computing systems (12+ layer boards, >1000 pin BGAs) • Optimize signal integrity for high-frequency AI processor interfaces (DDR4/DDR5, HBM2/HBM3) • Design and validate high-speed differential pairs for AI accelerator communication buses • Implement advanced routing techniques for minimizing crosstalk in dense AI computing layouts • Perform pre-silicon signal integrity analysis using industry-standard simulation tools Thermal Management & Power Delivery • Design sophisticated thermal solutions for high-power AI processors (300W+ TDP) • Develop power delivery networks (PDN) for multi-rail AI systems with precise voltage regulation • Implement advanced cooling solutions including liquid cooling interfaces for AI applications • Optimize power efficiency for AI workloads through intelligent power management IC selection • Design thermal monitoring and protection circuits for AI hardware safety AI Hardware Validation & Testing • Develop comprehensive test strategies for AI hardware validation including ML benchmark testing • Perform hardware debugging using advanced tools (high-speed oscilloscopes, logic analyzers, thermal cameras) • Conduct AI workload stress testing and performance optimization • Validate AI hardware against industry standards (PCIe compliance, NVIDIA GPU specifications) • Execute EMI/EMC testing and mitigation for AI computing systems Cross-functional Collaboration • Collaborate with AI software teams to optimize hardware-software co-design for ML workloads • Work with mechanical engineers on thermal and form factor optimization for AI hardware • Partner with manufacturing teams to ensure AI hardware manufacturability and cost optimization • Support field deployment and troubleshooting of AI hardware systems Required Technical Skills & Experience Core AI Hardware Expertise • 6-10 years of experience in embedded/AI hardware design with focus on highperformance computing • Proven experience designing PCBs for GPU integration (NVIDIA GeForce, Quadro, Tesla series) • Hands-on experience with NPU and AI accelerator integration (Intel VPU, Google TPU, Qualcomm NPU) • Deep understanding of AI hardware architectures and computational requirements for ML workloads Advanced PCB Design Skills • Expert proficiency in professional PCB design tools: o Altium Designer (preferred for AI hardware complexity) o Cadence Allegro for high-speed digital design o Mentor Graphics PADS or KiCad for specific applications • Advanced knowledge of high-speed digital design principles and methodologies • Experience with signal integrity analysis tools (HyperLynx, SIwave, HFSS) • Expertise in power integrity analysis and PDN optimization AI-Specific Technical Requirements • Experience with high-bandwidth memory interfaces (HBM2, HBM3, GDDR6/6X) • Knowledge of AI interconnect standards (NVLink, PCIe Gen4/5, CXL, InfiniBand) • Understanding of AI processor power requirements and thermal design considerations • Familiarity with AI software frameworks (TensorFlow, PyTorch) and their hardware implications Hardware Design & Validation • Proficiency with hardware debugging and validation tools: o High-speed oscilloscopes (>10 GHz bandwidth) o Logic analyzers for AI bus protocol analysis o Thermal imaging cameras and power analyzers o JTAG debuggers and boundary scan tools • Experience with DFM/DFT practices for AI hardware manufacturing • Knowledge of EMI/EMC compliance for high-frequency AI systems Industry Standards & Compliance • Understanding of relevant industry standards: o PCI-SIG specifications (PCIe Gen4/5, CEM) o JEDEC standards for memory interfaces o IPC standards for PCB design and manufacturing o NVIDIA GPU design guidelines and AMD GPU specifications Must-Have Qualifications Educational Background • B.E./B.Tech in Electrical Engineering, Computer Engineering, or Electronics Engineering • M.E./M.Tech preferred with focus on VLSI Design, Computer Architecture, or AI Hardware Experience Requirements • Minimum 6 years of hands-on AI hardware or high-performance computing PCB design • At least 3 projects involving GPU or NPU integration from concept to production • Proven track record of AI hardware optimization for performance and power efficiency • Experience with AI hardware bring-up and system-level validation Technical Certifications (Preferred) • IPC Designer Certification (CID or CID+) • NVIDIA hardware partner certification • PCIe compliance testing experience • Altium Designer certification Preferred Qualifications Advanced AI Hardware Experience • Experience with FPGA-based AI acceleration (Xilinx Versal, Intel Stratix) • Knowledge of neuromorphic computing architectures and implementation • Familiarity with quantum computing hardware interfaces • Experience with AI chip design or custom ASIC integration Specialized Applications • Automotive AI hardware design with AEC-Q qualification • Data center AI infrastructure design and optimization • Edge AI systems with power and thermal constraints • AI camera systems with real-time processing requirements Advanced Tools & Technologies • Experience with AI hardware simulation tools (Ansys, Synopsys) • Knowledge of advanced cooling solutions (vapor chambers, liquid cooling) • Familiarity with AI benchmarking and performance analysis tools • Experience with hardware security for AI systems Industry Knowledge • Understanding of AI workload characteristics and hardware optimization • Knowledge of AI hardware trends and emerging technologies • Familiarity with AI hardware startups and ecosystem dynamics • Experience with AI hardware patents and intellectual property What We Offer • Opportunity to work on cutting-edge AI hardware that shapes the future of computing • Collaborative environment with leading AI researchers and engineers • Access to latest AI hardware development tools and technologies • Career growth path in the rapidly expanding AI hardware field • Competitive compensation • Professional development through conferences and training programs Eligibility Requirements • Legal authorization to work in the intended country • Ability to handle confidential and proprietary AI hardware designs • Willingness to travel for hardware validation and customer support (up to 20%) • Strong communication skills for cross-functional collaboration in AI project