Senior C++ Engineer - Autonomous Driving

Droisys; Sunnyvale (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Droisys in Sunnyvale, CA is seeking a seasoned C++ Developer to join our robotics software team. You will implement, debug, and test features in our production driving stack, collaborating with senior engineers to deliver reliable, high-quality code.

The role emphasizes motion planning concepts, real-time systems, and integration with ROS and simulation environments. A Bachelor's or Master's in CS/Robotics and 6+ years of experience are expected, with opportunities to shape next‑gen algorithmic

Qualifications

• Bachelor's or Master's degree in Computer Science, Robotics, or a related technical field.
• 6+ years of professional experience in software development.
• Strong proficiency in C++.
• Familiarity with motion planning and pathfinding (A*, RRTs, PRMs).
• Experience with large-scale codebases, Git, and software development workflows.
• Eagerness to learn and debug complex, real-time systems.

Responsibilities

• Implement, debug, and test features and modifications to driving behavior in production code base.
• Work closely with senior engineers to understand design specs and deliver reliable code.
• Utilize backend tooling to run regression tests and validate changes across driving scenarios.
• Participate in on-vehicle drive reviews to collect data and provide feedback on performance.

Skills

C++

Robotics

Motion planning

Large codebase

Git

Real-time systems

Education

Bachelor's or master's in CS/Robotics

Tools

ROS

CUDA

Simulation

Job description

Droisys in Sunnyvale, CA is seeking a seasoned C++ Developer to join our robotics software team. You will implement, debug, and test features in our production driving stack, collaborating with senior engineers to deliver reliable, high-quality code.

The role emphasizes motion planning concepts, real-time systems, and integration with ROS and simulation environments. A Bachelor's or Master's in CS/Robotics and 6+ years of experience are expected, with opportunities to shape next‑gen algorithmic