Artificial Intelligence Engineer

Physical AI Engineer (PhD Required)Onsite - San JoseAbout the RoleWe are seeking a PhD-level Physical AI Engineer to help define the next generation of intelligent computing platforms for robotics, industrial automation, machine vision, autonomous systems, and edge AI.This role will drive system architecture and workload analysis across heterogeneous computing platforms that combine CPUs, DSPs, FPGA fabric, AI accelerators, GPUs, memory subsystems, and high-speed sensor interfaces. You will focus on mapping real-world Physical AI workloads to optimized hardware and software architectures while influencing future platform and silicon roadmaps.As a member of an advanced architecture team, you will collaborate across CPU, GPU, real-time processing, video, embedded systems, and AI technologies to shape next-generation heterogeneous computing platforms. This is a highly visible technical leadership opportunity focused on defining future intelligent systems and programmable computing architectures.Key ResponsibilitiesDefine end-to-end sensor-to-actuator Physical AI reference architectures.Analyze and partition AI, computer vision, perception, planning, and control workloads across CPUs, DSPs, FPGAs, GPUs, and AI accelerators.Evaluate architecture tradeoffs involving performance, latency, power efficiency, memory bandwidth, scalability, and deterministic execution.Develop workload models, benchmarks, and performance projections for robotics, autonomous systems, and edge AI applications.Collaborate with engineering teams, customers, and ecosystem partners to identify future platform requirements.Influence next-generation SoC, FPGA, accelerator, memory, and interconnect architectures.Required QualificationsPhD in Electrical Engineering, Computer Engineering, Computer Science, Robotics, or a related technical discipline.Experience in system architecture, embedded computing, heterogeneous computing, robotics, AI acceleration, or advanced compute platforms.Strong understanding of heterogeneous compute architectures including:CPUsDSPsFPGAsGPUsAI/ML acceleratorsMemory subsystemsHigh-speed interconnectsExperience with one or more of the following:Artificial Intelligence / Machine LearningComputer VisionRoboticsAutonomous SystemsEdge AIDemonstrated technical leadership with the ability to influence architecture decisions and long-term technology strategy.Preferred QualificationsExperience with ROS2, edge AI frameworks, industrial robotics, machine vision, or autonomous platforms.Knowledge of FPGA-based acceleration and heterogeneous computing systems.Publications, patents, or recognized technical contributions in AI, robotics, computer architecture, or embedded systems.Experience modeling performance, latency, memory bandwidth, and power efficiency for complex AI workloads.This version reads more like a high-end semiconductor architecture position and is suitable for posting without revealing the client while emphasizing the caliber of candidate you're targeting.