Generative AI / Machine Learning Test Automation Engineer

Overview

Job Description :

• Develop AI solutions and intelligent agents tailored to automotive use cases.
• Automated generation of new test cases and gap analysis based on data analysis and specific requirements.
• Automated generation of new test cases based on data analysis and specific requirements.
• Design and build web applications using Python and modern web frameworks.
• Implement web services and APIs (e.g., Django REST Framework, FastAPI, Flask).
• Develop RAG applications that leverage automotive knowledge bases and document sources.
• Integrate and manage LLMs using AWS Bedrock and Amazon SageMaker for inference and fine-tuning.
• Fine-tune AI / LLM models for domain-specific performance and accuracy.
• Test, deploy, monitor, and maintain AI systems in production environments.
• Collaborate closely with data scientists and automotive engineers (HIL Tester, Feature Owners) to integrate AI into system architectures.
• Continuously monitor AI research, industry trends, best practices, and relevant regulations.
• Develop automated test cases, tools, and processes using object-oriented programming and / or AI or Machine-Learning frameworks.
• Test Automation using Python, C#, ECU Test etc.
• Good Experience in HIL Validation Platforms like DSPACE, In-Vehicle Automation Testing, experience in Testing Tools like Vector CANOE, CANALYZER, etc.
• Good Experience / Knowledge working on Issue management, Defect Management, and Version Management tools like JIRA, GitHub, SVN, etc.
• Good Knowledge of UDS Protocol, Validating Diag over CAN, DOIP, CAN, LIN Protocols, etc.
• Knowledge of ECU Test, CAPL Scripting, etc. would be an added advantage
• Should be able to support the DevOps Team in developing scripts for CI / CD using Python and validating the same

Tools

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