Robotics & Autonomy Systems Architect

About the role

The is responsible for analyzing the full stack of modern robotics and drone systems, encompassing sensing, perception, planning, control, and onboard compute. In this position, you will own the critical translation of high-level autonomy requirements into concrete system-level compute architectures that are reliable, efficient, and performant. You will own the evaluation of real-world deployment constraints, ensuring that robotics systems meet stringent standards for reliability, real-time performance, safety, and energy efficiency. You will own the collaboration across hardware, software, and system architecture teams to define optimized compute solutions for robotics and embodied AI workloads. You will own the development of detailed system-level workload models that accurately represent diverse robotics and drone use cases. You will own the guidance of product direction by identifying emerging requirements across mobile robots, AMRs, drones, and other embodied AI systems. You will own the alignment of AI model workflows with next-generation hardware capabilities to ensure seamless integration. You will own the mapping of robotics and autonomy workloads onto target compute platforms, identifying critical performance, latency, and power constraints.

Key facts

What you'll do

• Evaluate and analyze modern robotics and drone system architectures, including sensing, perception, planning, control, and onboard compute subsystems.
• Interpret and process the requirements of autonomy stacks, translating abstract algorithmic needs into concrete system-level compute specifications.
• Map and assess robotics and autonomy workloads onto available compute platforms, rigorously identifying performance, latency, and power constraints.
• Collaborate closely with hardware architects to define and refine compute architectures that are specifically optimized for robotics and embodied AI workloads.
• Evaluate real-world deployment requirements for robotics systems, focusing on reliability, real-time performance, safety, and energy efficiency metrics.
• Collaborate with AI model architects and silicon designers to ensure alignment and optimization of robotics workloads with next-generation hardware capabilities.
• Develop detailed system-level workload models that accurately represent complex robotics and drone use cases for analysis and planning.
• Guide strategic product direction by identifying and articulating emerging requirements across robotics, AMRs, drones, and other embodied AI systems.
• Assess the suitability of robotics frameworks such as ROS and Isaac for specific autonomy pipeline requirements.
• Analyze sensor modality requirements, including cameras, lidar, radar, and IMUs, for integration into compute architectures.
• Evaluate the needs of real-time systems and robotics control loops within the context of compute platform constraints.
• Assess the implications of drones, autonomous vehicles, and industrial robotics on compute architecture decisions.
• Analyze how AI model integration and inference workloads impact the requirements for robotics pipelines and hardware.
• Conduct system-level performance reasoning to balance compute, memory, and power across the entire autonomy stack.
• Evaluate the trade-offs between centralized and distributed compute architectures for robotic deployments.
• Assess the impact of communication protocols and data throughput requirements on system design.
• Perform detailed analysis of power budgets and their relationship to compute performance in mobile robotic platforms.
• Identify gaps in current compute platforms that hinder the deployment of advanced robotics and autonomy features.
• Define compute architecture roadmaps that support the evolution of Velaura's robotics and autonomy products.
• Partner with cross-functional teams to ensure system-level designs meet market needs and technical constraints.

Requirements

• You need a Strong understanding of robotics or drone system architectures, including the interaction between hardware and software layers.
• You need experience working with autonomy stacks, including perception, sensor fusion, planning, and control functions.
• You need experience with robotics frameworks such as ROS and Isaac or similar autonomy platforms and tools.
• You need a Strong systems engineering mindset and the ability to reason about end-to-end system performance from sensors to actuators.
• You need experience deploying or architecting compute platforms specifically designed for robotics or autonomous systems.
• You need the ability to work effectively across hardware, software, and system architecture teams, bridging technical domains.
• You need Experience designing compute architectures for robotics or edge AI systems to meet strict performance and power targets.
• You need Familiarity with common sensor modalities such as cameras, lidar, radar, and IMUs and their data processing requirements.

Nice to have

• It helps if you have Experience with real-time systems and the constraints of robotics control loops.
• It helps if you have Experience with drones, autonomous vehicles, or industrial robotics platforms.
• It helps if you have Experience with how AI models are integrated into robotics pipelines and deployed at the edge.
• It helps if you have Experience with simulation tools and environments used for robotics autonomy testing.
• It helps if you have Experience with safety-critical systems and functional safety considerations for robotics.
• It helps if you have Experience with networking and communication protocols in distributed robotic systems.
• It helps if you have Experience with power management techniques for battery-operated autonomous systems.
• It helps if you have Experience with cloud robotics concepts and hybrid compute architectures.
• It helps if you have Experience with machine learning operations (MLOps) for edge deployment.
• It helps if you have Experience with containerization and orchestration platforms in robotics environments.

Practical notes

This role requires the ability to analyze modern robotics and drone system architectures including sensing, perception, planning, control, and onboard compute. You will understand how autonomy stacks process sensor data and translate requirements into system-level compute needs. You will map robotics and autonomy workloads onto compute platforms, identifying performance, latency, and power constraints. You will work with hardware architects to define compute architectures optimized for robotics and embodied AI workloads. You will evaluate real-world deployment requirements for robotics systems including reliability, real-time performance, safety, and energy efficiency. You will collaborate with AI model architects and silicon designers to align robotics workloads with next-generation hardware capabilities. You will develop system-level workload models representing robotics and drone use cases. You will guide product direction by identifying emerging requirements across robotics AMRs, drones, and other embodied AI systems.