Role: Principal Engineer, AI Hardware Modeling
Work location: Mountain View, CA – Onsite
Contract
Job Description:
“The Principal Engineer, AI Hardware Modeling (NPU), within the NPU Hardware & Software organization, is a senior individual contributor role for an engineer with deep expertise in hardware modeling, emulation, and hardware–software co-design. This role provides expert-level technical leadership in developing and maintaining bit-accurate and cycle-accurate hardware models that represent complex AI accelerator and NPU architectures used in ADAS, autonomous driving, and in-vehicle AI platforms.
This role owns the architecture and evolution of hardware modeling frameworks, translates conceptual hardware designs into robust, scalable software models, and enables early software development, verification, and performance analysis ahead of silicon availability. The Principal Engineer, AI Hardware Modeling (NPU) operates with a high degree of autonomy, partners closely with architecture, RTL, verification, and software teams, and influences modeling methodologies across client hardware programs.
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What are the Mandatory skills and skill proficiencies required for this position?
“General Skills:
• Expert communicator across global, cross-cultural, and cross-functional teams.
• Strong analytical, debugging, and system-level problem-solving skills.
• Proven ability to lead complex technical initiatives without direct authority.
• Quality-driven mindset with a strong focus on correctness, robustness, and coverage.
• Collaborative approach across hardware, software, verification, and safety organizations.
Required Specialized Skills:
• Extensive expertise in C/C++ programming for hardware modeling and simulation.
• Strong understanding of NPU or AI accelerator architectures, memory systems, and dataflow.
• Solid grounding in computer architecture and digital design principles.
• Experience with SystemC, transaction-level modeling (TLM), and/or hardware description languages.
• Familiarity with modern software development practices, including version control, testing, and CI pipelines. • Proven experience with bit-accurate and cycle-accurate modeling and hardware–software co-design methodologies. • Proficiency in performance optimization and memory management for large-scale software systems
Required Education: Bachelor’s degree in Electrical Engineering or Computer Engineering
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What are the Optional skills and skill proficiencies for this position?
“Desired Skills:
• Prior experience modeling AI accelerators, NPUs, GPUs, or similar compute architectures.
• Knowledge of automotive hardware requirements and functional safety concepts.
• Experience with FPGA prototyping, emulation, or hardware-in-the-loop validation.
• Background in parallel computing and high-performance simulation.
• Contributions to open-source modeling frameworks or relevant technical publications.
• Exposure to GenAI-assisted engineering tools and AI-augmented development workflows.
Desired Education: Master’s degree in Electrical Engineering or Computer Engineering
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