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AMD

Designs chips for computers and AI systems

System Architect - Industrial Robotics, Healthcare

Hardware Systems IntegrationConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Demonstrated experience owning system architecture documents, specifications, and system-level technical requirements.
  • Strong understanding of heterogeneous compute architectures incorporating CPUs, GPUs, NPUs, FPGAs, embedded processors, MCUs, and dedicated accelerators.
  • Practical knowledge of FPGA and adaptive SoC architectures and modern programmable logic design methodologies.
  • Experience with embedded systems development using C/C++, Python, embedded Linux, device drivers, Yocto, Buildroot, or comparable environments.
  • Experience with robotics and real-time control systems, including motor control, torque control, impedance control, multi-rate control loops, sensor acquisition, and deterministic scheduling.
  • Knowledge of industrial and embedded interfaces such as EtherCAT, CAN-FD, CANopen, SPI, I²C, Ethernet, PCIe, MIPI, and USB.
  • Understanding of system safety and reliability concepts, including watchdogs, safe states, diagnostics, fault detection, timeout handling, and applicable standards such as IEC 61508, ISO 26262, ISO 13849, and IEC 62304.
  • Experience with AI and edge inference technologies.
  • Familiarity with AI deployment frameworks and runtimes such as ONNX, PyTorch, TensorFlow, or comparable technologies.
  • Knowledge and understanding of agentic AI concepts and architectures.
  • Experience making hardware, software, and AI workload-partitioning decisions.
  • Ability to define and analyze interface, timing, latency, bandwidth, and memory budgets.
  • Experience conducting architecture trade-off analyses across multiple implementation options.
  • Demonstrated ability to support engineering teams beyond the initial architecture and concept phases.
  • Ability to explain architectural decisions using measurable technical criteria.
  • A Master’s degree or PhD in Electrical/Electronic Engineering, Computer Engineering, Computer Science, Robotics, or a related technical discipline is preferred; equivalent professional experience may be considered.

Responsibilities

  • Define end-to-end system architectures for AI-enabled embedded, robotics, industrial, and healthcare applications.
  • Partition workloads across CPU, GPU, NPU, FPGA programmable logic, AI Engines, MCUs, and external accelerators.
  • Architect AI inference pipelines for vision, sensor processing, robotics, and edge intelligence applications.
  • Evaluate architectural trade-offs involving latency, throughput, determinism, memory bandwidth, power, thermal constraints, functional safety, cost, and scalability.
  • Develop system architecture specifications, data-flow diagrams, interface definitions, timing budgets, memory and bandwidth requirements, and implementation guidance.
  • Partner with FPGA, software, firmware, AI, and system engineering teams to translate architecture concepts into executable designs.
  • Review technical proposals and challenge assumptions using engineering analysis and measurable data.
  • Support customer-facing technical discussions by providing clear and credible system architecture guidance.
  • Guide proof-of-concepts, benchmarks, reference designs, and technical demonstrators.
  • Identify system-level architectural risks early and recommend practical mitigation strategies.
  • Travel approximately 25% to support onsite customer meetings and engagements.

About the Company

AMD

Designs chips for computers and AI systems

AMD designs processors, graphics chips and AI accelerators for computer makers, cloud operators and businesses that build electronic devices. Its Ryzen processors power personal computers, while EPYC processors handle work in data centers and Radeon chips render graphics. Instinct accelerators run AI models, paired with software that developers use to train models and put them into production. AMD sells chips and related computing systems through equipment makers, distributors and retail channels, and contracts with outside foundries to fabricate its semiconductor designs. It was founded in 1969 and has its headquarters in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1969

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