Senior Test Developer – Automotive Simulation Testing & Failure-Triage Lead

NVIDIA AI; Pune District; On-site; INR 1,400,000 - 2,800,000; Full time

Job summary

NVIDIA AI is seeking an experienced automotive software testing and validation specialist to lead pre-merge testing, triage failures, and drive continuous improvement for ADAS validation. The role emphasizes Python automation, bisection using Git and CI/CD, and collaboration across multisilo teams to ensure robust verification across L2/L3 features.

The candidate will mentor engineers, produce actionable diagnostics, and advance agentic AI workflows for efficient triage and root-cause analysis

Qualifications

• B.Tech. or equivalent degree in CS, CE, ECE, EEE, Automotive Engineering, or a related field, with 8-12 years of relevant automotive software testing and validation experience.
• Strong expertise in HIL/SIL, simulation testing, automotive verification workflows, and root-cause analysis using signals, logs, traces, and system-level evidence.
• Hands-on validation experience with ADAS and automated-driving functions, including L2, L2PP, and L3/L4 features across perception, localization, prediction, planning, control, and vehicle interfaces.
• Advanced Python skills for automation, signal processing, data analysis, visualization, debugging, and validation-tool development.
• Proven expertise in bisection using Git, CI/CD pipelines, build artifacts, and change history to identify and validate culprit CLs.
• Demonstrated ability to apply Agentic AI workflows.
• Proven ability to lead small to mid-sized teams, work with diverse stakeholders, and drive process alignment and continuous improvement.
• Excellent communication, documentation, and stakeholder management skills, with the ability to break down complex process topics into actionable steps.

Responsibilities

• Lead daily pre-merge testing, simulation failure triage, task prioritization, team execution, and timely closure of critical issues.
• Perform root-cause and signal-level analysis using logs, traces, metrics, videos, and state transitions to isolate software, simulation, configuration, infrastructure, analyzer, or evaluator failures.
• Lead the bisections using source-control history, failure patterns, signal evidence, and code-impact analysis to identify culprit CLs and complex multi-change regressions.
• Develop Python-based tools and automation for log analysis, failure classification, regression isolation, automated bisection, and reporting.
• Apply Agentic AI workflows to correlate diagnostic evidence, identify patterns, summarize failures, recommend investigation paths, and improve triage efficiency.
• Collaborate with development, systems, simulation, validation, tools, and infrastructure teams; track quality metrics, communicate risks, mentor engineers, and establish consistent triage practices.

Skills

Python automation

Root-cause analysis

ADAS testing

L2/L3 features

Team leadership

Communication

Education

B.Tech./equivalent in CS/CE/ECE/EEE/Automotive Engineering

Tools

Git

GitLab CI

Jenkins

Docker

Kubernetes

Job description

Full time

What You'll Be Doing

• Lead daily pre-merge testing, simulation failure triage, task prioritization, team execution, and timely closure of critical issues.
• Perform root-cause and signal-level analysis using logs, traces, metrics, videos, and state transitions to isolate software, simulation, configuration, infrastructure, analyzer, or evaluator failures.
• Lead the bisections using source-control history, failure patterns, signal evidence, and code-impact analysis to identify culprit CLs and complex multi-change regressions.
• Develop Python-based tools and automation for log analysis, failure classification, regression isolation, automated bisection, and reporting.
• Apply Agentic AI workflows to correlate diagnostic evidence, identify patterns, summarize failures, recommend investigation paths, and improve triage efficiency.
• Collaborate with development, systems, simulation, validation, tools, and infrastructure teams; track quality metrics, communicate risks, mentor engineers, and establish consistent triage practices.

What We Need To See

• B.Tech. or equivalent degree in CS, CE, ECE, EEE, Automotive Engineering, or a related field, with 8-12 years of relevant automotive software testing and validation experience.
• Strong expertise in HIL/SIL, simulation testing, automotive verification workflows, and root-cause analysis using signals, logs, traces, and system-level evidence.
• Hands-on validation experience with ADAS and automated-driving functions, including L2, L2PP, and L3/L4 features across perception, localization, prediction, planning, control, and vehicle interfaces.
• Advanced Python skills for automation, signal processing, data analysis, visualization, debugging, and validation-tool development.
• Proven expertise in bisection using Git, CI/CD pipelines, build artifacts, and change history to identify and validate culprit CLs.
• Demonstrated ability to apply Agentic AI workflows.
• Proven ability to lead small to mid-sized teams, work with diverse stakeholders, and drive process alignment and continuous improvement.
• Excellent communication, documentation, and stakeholder management skills, with the ability to break down complex process topics into actionable steps.

Ways To Stand Out From The Crowd

• Experience applying AI agents or LLM-based workflows to log analysis, evidence correlation, failure classification, automated bisection, or root-cause investigation.
• Familiarity with GitLab CI, Jenkins, Linux, Docker, Kubernetes, cloud platforms, and large-scale simulation infrastructure..
• Working knowledge of Automotive SPICE (ASPICE) processes and Functional Safety (ISO 26262) requirements, with their application in ADAS software verification and validation.
• Good understanding of ADAS regulatory standards and consumer safety assessment protocols, including Euro NCAP, UNECE DCAS, GSR, and applicable UNECE homologation regulations.
• Prior experience owning a validation, failure-triage, bisection, or pre-merge quality program and delivering continuous improvements end-to-end.

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