- Key Responsibilities
- Define validation strategies, plans, acceptance criteria, and coverage goals for autonomous and AI-enabled functions.
- Analyze system, functional, scenario, safety, and regulatory requirements and translate them into traceable test cases.
- Create, review, maintain, and execute manual and automated test cases across component, subsystem, integration, and vehicle levels.
- Develop reusable test automation frameworks, scripts, utilities, reporting workflows, and continuous validation pipelines.
- Build and execute simulation scenarios using IPG CarMaker, CARLA, and comparable virtual validation environments.
- Perform scenario-based testing across normal, edge, corner, degraded, and failure conditions, including parameter variation and large-scale regression campaigns.
- Validate the end-to-end stack, including sensor inputs, perception, localization, prediction, planning, control, and vehicle or actuator response.
- Evaluate AI model and system behavior for accuracy, robustness, consistency, explainability, performance limitations, and operational-design-domain constraints.
- Analyze logs, metrics, test results, and failures; isolate root causes and work with systems, AI/ML, simulation, software, controls, and safety teams to drive closure.
- Maintain requirements-to-test traceability, evidence, dashboards, defect records, validation reports, and release-readiness recommendations.
- Contribute to audit-ready validation evidence and demonstrate compliance with applicable engineering standards, internal processes, and regulatory expectations.

- Required Experience and Qualifications
- Robust domain experience in autonomous driving, ADAS, robotics, intelligent mobility, or a closely related AI-enabled system domain.
- Demonstrated experience in validation and verification of complex, safety-relevant systems.
- Hands-on experience in test design,



test-case creation, requirements-based testing, scenario-based testing, and test automation.
- Extensive working experience with simulation platforms, particularly IPG CarMaker and CARLA.
- Experience validating end-to-end autonomous-system behavior rather than isolated algorithms alone.
- Good understanding of the autonomous-driving stack: sensing, perception, sensor fusion, localization, prediction, planning, control, and actuation.
- Experience with result analysis, defect triage, root-cause investigation, coverage assessment, and technical reporting.
- Working knowledge of automotive safety, SOTIF, cybersecurity, homologation, data governance, and AI-related compliance considerations relevant to validation.
- Ability to collaborate across multidisciplinary engineering teams and communicate validation risks, gaps, and evidence clearly.

- Preferred Technical Exposure
- Python or another scripting language for test automation, data analysis, orchestration, and report generation.
- Model-in-the-loop, software-in-the-loop, hardware-in-the-loop, vehicle-in-the-loop, and scenario-in-the-loop validation methods.
- OpenSCENARIO, OpenDRIVE, road-network modelling, scenario generation, replay, parameter sweeps, and synthetic-data workflows.
- CI/CD integration, automated regression, distributed simulation, cloud-based execution, and test management tools.
- Quantitative validation metrics for detection, tracking, localization, planning, control, safety, comfort, and system performance.
- AI assurance topics such as dataset representativeness, bias and performance analysis, robustness, model limitations, traceability, monitoring, and change impact.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Autonomous AI Validation with IPG CarMaker, CARLA Experts (Bengaluru)
🏢 KPIT
📍 Bengaluru