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Robotics and Autonomy Systems Architect

Summary

Designs compute architectures for robotics and drones, mapping autonomy workloads to hardware while balancing latency, power, and safety constraints.

You analyze robotics and drone architectures across sensing, perception, planning, control, and onboard compute. You map autonomy workloads to compute platforms, evaluate performance, latency, power, reliability, and safety requirements, develop workload models, and help define architectures for robotics, drones, and embodied AI.

Responsibilities

  • Analyze robotics and drone system architectures
  • Understand how autonomy stacks process sensor data
  • Translate sensor-processing requirements into system-level compute needs
  • Map robotics and autonomy workloads onto compute platforms
  • Identify performance, latency, and power constraints
  • Define compute architectures optimized for robotics and embodied AI workloads
  • Evaluate deployment requirements including reliability, real-time performance, safety, and energy efficiency
  • Collaborate with AI model architects and silicon designers
  • Develop system-level workload models for robotics and drone use cases
  • Identify emerging requirements across robotics, AMRs, drones, and embodied AI systems

Requirements

  • Strong understanding of robotics or drone system architectures
  • Experience with autonomy stacks including perception, sensor fusion, planning, and control
  • Experience with robotics frameworks such as ROS or Isaac
  • 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 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

Benefits

  • Performance-based incentives
  • Equity participation
  • Medical coverage
  • Dental coverage
  • Vision coverage
  • Paid time off
  • Flexible work arrangements
  • Professional development opportunities

See also

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