Drimva

Amazon

Senior Robotics SDE, Safe Autonomy, Compass

$168K–$227K

Pasadena, CA +1 · Senior · Full-time · Posted Sep 8, 2026

Location
Pasadena, CA
North Reading, MA
Experience
5+ years of non-internship professional software development; 5+ years programming; 5+ years leading design or architecture. Preferred: 5+ years of full software development life cycle experience.
Education
Master's or PhD in Robotics, Computer Science, Controls, or a related field (preferred).

About the job

Integrate Compass safety software across diverse robot platforms, building scalable real-time interfaces and validation systems for safe autonomy.

What you'll do

  • Design and maintain software integration layers, abstractions, and APIs for safety modules across robot platforms.
  • Collaborate with autonomy teams and integrate safety systems with motion planning, perception, controls, and safety-rated hardware and firmware.
  • Build testing and simulation validation pipelines, resolve real-time performance issues, and mentor engineers.

What they ask for

  • 5+ years of non-internship professional software development experience, including 5+ years programming in at least one language.
  • 5+ years leading design or architecture of new and existing systems.
  • Experience as a mentor, tech lead, or engineering team lead.
  • Proficiency in C++, Rust, and/or Python; experience developing for robotic, embedded, or safety-critical systems and designing multi-platform abstractions or APIs.

Nice to have

  • Master's or PhD in Robotics, Computer Science, Controls, or a related field.
  • Experience with control barrier functions, safety verification, RTOS, safety-rated firmware, multiple robot types, reinforcement learning, foundation models, or robotics simulation.

Pay

168,100.00 - 227,400.00 USD annually (base salary); 168,100.00 - 227,400.00 USD annually (base salary); 168,100.00 - 227,400.00 USD annually (base salary)

Tools

C++, Rust, Python, ROS/ROS2, RTOS, IEC 61508, ISO 13849

AI focus

Integrate safety with reinforcement learning and foundation models on robotic systems; experience deploying these is preferred.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)