Software Verification & Validation Engineer

Key Responsibilities

Performance Metrics Definition: Design, formalize, and implement quantitative safety and comfort metrics for AV algorithm modules (Perception, Prediction, Motion Planning, and Control). Translate high-level operational design domains (ODDs) and potential failure modes into automatable, objective criteria.

Simulation Test Engineering: Build, execute, and maintain complex open-loop and closed-loop simulation test suites to stress-test software releases, evaluate edge cases, and benchmark module-level and system-level performance.

Failure Triage & Root Cause Analysis: Analyze large-scale simulation outputs to distinguish genuine software regressions from simulation artifact anomalies. Localize root causes to specific modules and deliver actionable diagnostic reports to development teams.

Test Framework Automation: Write production-grade Python scripts and extend core testing frameworks to automate test execution, data ingestion, and statistical reporting.

Ci/cd

• Pipeline Integration: Integrate automated regression suites into continuous integration pipelines (e.g., Jenkins) for seamless, multi-stage testing across daily builds.
• Data-Driven Quality Standards: Establish reproducible testing practices, enforcing strict artifact hygiene, dependency management, and quantitative validation over visual inspection.