ADAS Senior Software tester

AVIN Systems Pvt Ltd; Pune District; In loco; INR 1.200.000 - 1.800.000; Tempo pieno

Descrizione del lavoro

AVIN Systems Pvt Ltd in Pune seeks an experienced ADAS validation engineer to lead requirement elicitation, write test specifications, and own the test strategy for vehicle-level requirements. You will supervise daily ADAS validation on simulation platforms across nominal, fault-injection, and performance scenarios.

You will drive failure triage end-to-end, perform root-cause analysis across logs and traces, and develop Python-based tooling for log analysis, automation, and reporting.

Competenze

• B.Tech. or equivalent degree in CS/CE/EC/EE/Automotive.
• 5–8 years in automotive software testing and validation.
• Strong expertise in HIL/SIL and simulation-based testing.
• Hands-on validation of ADAS across L2–L4 systems.
• Advanced Python for automation, data analysis, and reporting.
• Proficient in regression analysis and bisection using Git/CI/CD.
• Experience with ALM and requirements-tools (Jira/Jama/DOORS/Codebeamer).

Mansioni

• Lead requirement elicitation and write test specs and plans.
• Lead daily ADAS validation on simulation platforms across nominal, safety, fault-injection, and performance scenarios.
• Own failure triage and end-to-end technical assessment and closure.
• Analyze large-scale sensor/simulation data to identify failure trends and perform root-cause analysis.
• Lead bisections using source-control history and signal evidence to identify culprit CLs.
• Provide technical analysis of top bugs to stakeholders and publish quality reports.
• Design Python-based tools for log analysis, failure classification, regression isolation, and reporting.
• Apply Agentic AI workflows to correlate diagnostic evidence and improve triage efficiency.
• Track quality metrics, communicate risks, and mentor engineers.

Conoscenze

Python programming

Automation

Communication

Documentation

Root-cause analysis

Data analysis

Stakeholder management

Formazione

B.Tech. or equivalent in CS/CE/EC/EE/Automotive

Strumenti

Jira

Jama

DOORS

Codebeamer

Git

CI/CD

Linux

Docker

Kubernetes

Descrizione del lavoro

What you'll be doing:

• Lead requirement elicitation and own the writing of test specifications and test plans for applicable vehicle-level requirements. Create the test strategy document as per the standard STLC.
• Lead the daily execution of ADAS software validation on simulation platforms, covering nominal, safety, fault-injection, and performance scenarios across a feature or subsystem.
• Own failure triage and prioritization end-to-end technical assessment, issue tracking, stakeholder communication, and driving critical and high-impact issues through to closure.
• Analyze large-scale sensor and simulation data to identify failure trends and lead root-cause analysis across logs, traces, metrics, videos, and state transitions, isolating issues across software, simulation, configuration, infrastructure, analyzers, and evaluators.
• Lead bisections using source-control history, failure patterns, signal evidence, and code-impact analysis to identify culprit CLs and resolve complex multi-change regressions.
• Provide technical analysis of top bugs to cross-functional stakeholders including project management, hardware, and software teams, and periodically publish statistical quality reports.
• Design and build Python-based tools for log analysis, failure classification, regression isolation, automated bisection, and reporting — reusable infrastructure the broader team depends on.
• Apply Agentic AI workflows to correlate diagnostic evidence, identify patterns, summarize failures, recommend investigation paths, and improve team-wide triage efficiency.
• Track quality metrics, communicate risks, mentor engineers, and establish consistent triage practices across the team.

What we need to see:

• B.Tech. or equivalent degree in Computer Science, Computer Engineering, Electronics & Communication, Electrical Engineering, Automotive Engineering, or a related field, with 5–8 years of relevant experience in automotive software testing and validation.
• Strong expertise in HIL/SIL, simulation-based testing, automotive verification and validation workflows, and system-level root-cause analysis using signals, logs, traces, metrics, and other diagnostic evidence.
• Hands‑on experience validating ADAS and automated‑driving functions, including L2, L2++, L3, and/or L4 systems, across domains such as perception, localization, prediction, planning, control, and vehicle interfaces.
• Advanced Python programming skills with hands‑on experience developing automation for data and signal analysis, visualization, debugging, validation tooling, failure classification, and reporting.
• Proven expertise in regression analysis and automated/manual bisection using Git, CI/CD pipelines, build artifacts, source‑control history, and change analysis to identify, isolate, and validate culprit change lists (CLs).
• Demonstrated ability to apply Agentic AI workflows to engineering and validation problems, including diagnostic evidence correlation, failure analysis, pattern identification, investigation support, and automation of repetitive triage activities.
• Strong communication, technical documentation, and stakeholder‑management skills, with the ability to translate complex technical and process topics into clear, actionable steps and decisions.
• Hands‑on experience with Application Lifecycle Management (ALM) and requirements‑management tools, such as Jira, Jama, DOORS, Codebeamer, or equivalent platforms.

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.
• Any certification course on Machine learning / Self‑driving car.