
Open since May 2026
Software Engineer, Verification and Validation (Perception)
AI Summary
Independently validates robotic perception software, designing test strategies and executing campaigns across simulation and real-world environments to ensure performance, robustness, and release readiness.
About this role
We are looking for a Software Engineer, Verification and Validation (V&V), Perception to join our Autonomy V&V team and help ensure the performance, robustness, and reliability of our robotic perception stack in real-world operating conditions. In this role, you will focus on the independent verification and validation of perception software that is designed and developed by our Perception team, helping provide objective assessment of system readiness, performance, and quality.
What You'll Get To Do:
Independently validate perception software developed by the Perception team
Evaluate perception software from a V&V perspective to ensure it meets system and product requirements.
Provide objective verification of functionality, robustness, and release readiness.
Work closely with developers while maintaining an independent quality and validation role.
Define validation strategies for perception systems
Create V&V plans for LiDAR, camera, GPS, and IMU-based perception systems across sensor, module, and system levels.
Convert product and engineering requirements into clear, testable validation criteria.
Establish performance metrics, quality gates, and release readiness criteria.
Design and execute perception test coverage
Develop test cases for nominal, edge-case, and degraded sensor conditions.
Validate performance across simulation, replay, and real-world test environments.
Ensure coverage across environmental, operational, and sensor failure scenarios.
Analyze failures using logs and datasets
Investigate issues using recorded sensor logs, replay tools, and annotated datasets.
Perform structured root-cause analysis on perception and sensor-related failures.
Partner with the Perception team to reproduce issues, clarify expected behavior, and verify fixes.
Build scalable validation and regression workflows
Improve repeatable validation through automation, replay, and simulation-based testing.
Support regression coverage across software releases and perception updates.
Contribute to clear reporting and measurable quality tracking.
Drive cross-functional release confidence
Collaborate with Perception, Autonomy, Systems, Hardware, and Field teams on validation priorities and readiness.
Communicate risks, findings, and recommendations to technical stakeholders.
Support data-driven release decisions with clear, independent validation evidence.
What You Bring:
Bachelor’s or Master’s degree in Robotics, Electrical Engineering, Computer Engineering, Computer Science, Mechanical Engineering, or a related technical field.
3+ years of experience in verification, validation, systems test, or perception evaluation for robotics, autonomous systems, automotive, or similar domains.
Experience working with robotic sensors such as LiDAR, cameras, GPS, and IMUs.
Strong understanding of perception system behavior, sensor limitations, and common failure modes.
Experience developing test plans, validation procedures, performance metrics, and structured test reports.
Experience analyzing logs, datasets, and field results to debug issues and perform root-cause analysis.
Strong cross-functional communication skills and the ability to work effectively with development teams while representing an independent V&V function.
What Sets You Apart:
Experience validating perception systems for autonomous vehicles, mobile robots, drones, industrial robots, or defense robotics platforms.
Familiarity with perception workflows such as detection, tracking, localization, mapping, or sensor fusion.
Experience with simulation, software-in-the-loop, hardware-in-the-loop, and replay-based validation.
Experience with sensor calibration, synchronization, time alignment, and sensor health monitoring.
Experience building automated regression tools or validation infrastructure.
Familiarity with annotated datasets, ground-truth generation, and scenario-based test design.
Knowledge of structured verification processes, requirements traceability, and safety-oriented development practices.
Skills
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