Auradine

Robotics and Autonomy Systems Architect

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You will analyze robotics and drone system architectures from sensors and perception pipelines through planning, control, and onboard compute. You will translate autonomy stack requirements into system and hardware architectures, map workloads to compute platforms, evaluate real-world deployment constraints (latency, power, reliability, safety), develop system-level workload models, and collaborate with hardware and AI model architects to align robotics workloads with next-generation compute.

Responsibilities

  • Analyze modern robotics and drone system architectures, including sensing, perception, planning, control, and onboard compute.
  • Understand how autonomy stacks process sensor data and translate those requirements into system-level compute needs.
  • Map robotics and autonomy workloads onto compute platforms, identifying performance, latency, and power constraints.
  • Work with hardware architects to define compute architectures optimized for robotics and embodied AI workloads.
  • Evaluate real-world deployment requirements for robotics systems, including reliability, real-time performance, safety, and energy efficiency.
  • Collaborate with AI model architects and silicon designers to align robotics workloads with next-generation hardware capabilities.
  • Develop system-level workload models representing robotics and drone use cases.
  • Help guide product direction by identifying emerging requirements across robotics, AMRs, drones, and other embodied AI systems.

Requirements

  • Strong understanding of robotics or drone system architectures.
  • Experience working with autonomy stacks including perception, sensor fusion, planning, and control.
  • Experience with robotics frameworks such as ROS, Isaac, or similar autonomy platforms.
  • Strong systems engineering mindset and ability to reason about end-to-end system performance.
  • Experience deploying or architecting compute platforms for robotics or autonomous systems.
  • Ability to work across hardware, software, and system architecture teams.
  • Experience designing compute architectures for robotics or edge AI systems.
  • Familiarity with sensor modalities such as cameras, lidar, radar, and IMUs.
  • Experience with real-time systems and robotics control loops.
  • Experience with drones, autonomous vehicles, or industrial robotics.
  • Understanding of how AI models integrate into robotics pipelines.