Lead Autonomy Software Engineer for Pilot Assist Robotics

Jobtailor

San Carlos (CA)

On-site

USD 150,000 - 210,000

Full time

11 days ago

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Job summary

Jobtailor in San Carlos, CA is seeking a senior robotics software engineer to design, build, and deploy embedded software powering advanced pilot assistance systems. You will own autonomy features from concept through deployment, focusing on reliability and performance within production environments.

Requirements include 5+ years in robotic/embedded software, strong C++/Python skills, real-time systems experience, and familiarity with ROS or DDS.

Qualifications

5+ years designing and deploying robotic software/embedded systems in production environments.
Strong software engineering skills in C++ and/or Python.
Experience with systems-level or embedded programming.
Experience building real-time or interactive systems for time-sensitive decisions.
Familiarity with autonomy systems such as planning, decision-making, or reasoning.
Experience integrating with perception or sensor pipelines.
Hands-on experience with embedded or edge compute platforms.
Experience debugging hardware/software interactions.
Ability to deliver complex systems end-to-end in fast-moving environments.
Experience with safety-critical or mission-critical systems (aviation or robotics a bonus).
Familiarity with ROS or DDS is a bonus.
Experience with human operators in the loop, simulations or real-time control is a bonus.
Must be a U.S. Person and authorized to work in the United States.
No visa sponsorship or transfers available.
Must work on-site in San Carlos, CA at least 3 days/week or willing to relocate.

Responsibilities

Design, build, and deploy robotic and embedded software powering pilot assistance systems in production environments.
Own autonomy-related features from concept to deployment with emphasis on reliability and performance.
Write, review, and maintain Python and C++ code across autonomy, systems, and embedded components.
Integrate software with hardware, sensors, and perception or data pipelines for autonomous decision-making.
Optimize software for edge compute environments, including latency and resource use, with safety mechanisms.
Lead testing, validation, and deployment to meet safety-critical requirements.
Mentor engineers and contribute to technical direction through design and code reviews.