Software Engineer

Perrone Robotics, Inc.; Charlottesville (VA); On-site; USD 110,000 - 160,000; Full time

Job summary

Perrone Robotics, Inc. is seeking a Software Engineer for Autonomous Vehicle Systems in Charlottesville, VA. You will own core autonomy software across our TONY AV Kit platform, including vehicle control, safety interlocks, perception integration, and route/mapping logic.

You’ll work with hardware and field engineers to diagnose and resolve deployed-vehicle issues. Responsibilities include safety-critical control, PID tuning, sensor integration, log analysis, platform provisioning, and

Qualifications

• Strong proficiency in Java and/or C++ (or comparable systems languages) for real-time or near-real-time control software.
• Experience with production software deployment and release management practices.
• Comfortable reading and diagnosing issues from detailed system logs and field data.
• Excellent cross-functional communication with hardware, QA, and operators.
• Able to travel 10% for field deployments and testing.

Responsibilities

• Safety-critical control software: design, implement, and review safety interlock and watchdog logic for the vehicle control stack across hardware platforms.
• Vehicle dynamics tuning: tune speed control, braking, and steering PID loops for smooth, predictable behavior.
• Perception and sensor integration: integrate LiDAR, RADAR, GPS/INS, parse NMEA/GNSS, diagnose sensor issues.
• Field defect diagnosis: analyze logs from deployed vehicles to root-cause issues and drive fixes with field/hardware teams.
• New platform provisioning: configure and deploy software stack onto new vehicle platforms and support simulation environments.
• Software deployment and production support: own release/configuration management and coordinate fixes with the engineering team.
• Cross-functional collaboration: work with hardware/field engineers to reproduce issues and translate feedback into engineering requirements.

Skills

Java/C++

Education

BSc/MSc in CS/Robotics/EE

Tools

Claude Code

Job description

Software Engineer, Autonomous Vehicle Systems

Reports To: GM/VP Automated Transit

Employment Type: Full-Time

About the Role

Perrone Robotics is looking for a software engineer, based out of our Charlottesville, VA office, to own core autonomy software across our TONY AV Kit platform, including vehicle control, safety interlocks, perception integration, and route and mapping logic. This role owns the software that keeps autonomous vehicles safe, accurate, and deployable across a growing fleet, from low-level safety watchdogs to path planning and sensor fusion, and works closely with hardware and field engineers to diagnose and resolve issues on deployed vehicles.

What You'll Do

Safety-critical control software: Design, implement, and review safety interlock and watchdog logic (arm/disarm signals, auto/manual transitions, fail-safe behavior) for the vehicle control stack across multiple hardware platforms.

Vehicle dynamics tuning: Tune speed control, braking, and steering PID loops to deliver smooth, predictable behavior, including hill-hold, downhill braking assist, and stop-point accuracy.

Perception and sensor integration: Integrate and calibrate LiDAR, RADAR, and GPS/INS sensors, parse and extend NMEA/GNSS message handling, and diagnose sensor timeout, calibration, and fusion issues from field logs.

Field defect diagnosis: Analyze logs from deployed vehicles to root-cause reported issues (unexpected slowdowns, steering loss, signal degradation, sensor timeouts) and drive fixes from diagnosis to resolution, partnering with field and hardware engineers who have physical access to the vehicles.

New platform provisioning: Configure and deploy the software stack (controls, self-navigation, obstacle detection and avoidance, diagnostics, tablet/UI) onto new vehicle platforms as they come online, and support simulation environments used for pre-deployment validation.

Software deployment and production support: Own release and configuration management for software running on the deployed fleet, troubleshoot production issues that surface in the field, and coordinate fixes and rollouts with the broader engineering team.

Cross-functional collaboration: Work directly with hardware and field engineers to reproduce and resolve issues that span software and hardware, such as steering feedback signal loss, actuator behavior, and brake tuning, and translate field and operator feedback into concrete engineering requirements.

Required Skills & Experience

Strong proficiency in Java and/or C++ (or comparable systems languages) for real-time or near-real-time control software.

Comfortable using AI-assisted development tools such as Claude Code to speed up coding, debugging, and log analysis work.

Comfortable reading and diagnosing issues from detailed system logs, including root-causing intermittent or hard-to-reproduce field issues.

Strong cross-functional communication skills, comfortable working with hardware engineers, QA, and vehicle operators to resolve issues that span disciplines.

Familiarity with production software deployment and release management practices.

Preferred Qualifications

Professional software engineering experience, ideally in robotics, autonomous vehicles, or safety-critical embedded systems.

Experience with autonomous vehicle software stacks, ADAS, or robotics middleware.

Experience with vehicle control systems, including PID tuning, actuator control, safety interlocks and watchdogs, and fail-safe design.

Experience integrating and calibrating perception sensors (LiDAR, RADAR, GPS/INS) and working with raw sensor protocols such as NMEA, CAN, and Modbus.

Experience with simulation tools or environments used for autonomous systems validation.

Familiarity with government or transit contracting environments and formal safety/QA documentation processes.

Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field, or equivalent experience.

Able to travel occasionally (roughly 10% of the time) to support field deployments and testing.

What Success Looks Like

Safety-critical control logic is robust, well-tested, and documented, with fail-safe behavior verified before deployment.

Field-reported defects are diagnosed quickly from logs and resolved with clear root cause analysis.

New vehicle platforms are brought online smoothly, with software configured, tuned, and validated ahead of deployment.

Production software releases roll out cleanly across the fleet, with issues caught and resolved with minimal downtime.