Job Duties:

Design, develop, and test infotainment system software in alignment with system architecture and program requirements.

Implement and optimize test automation frameworks to ensure reproducibility across connectivity, navigation, and voice functions.

Develop automation scripts and testing tools for automotive and AI platforms, applying debugging methodologies and validation practices.

Build and maintain scalable ML model training infrastructure using PyTorch/TensorFlow, GCP, and GPU utilization to support distributed training and deployment.

Fine-tune and deploy Transformer/LLM-based models, integrating natural language processing capabilities into infotainment features.

Collaborate with cross-functional teams to integrate third-party software and hardware, ensuring compliance with automotive communication protocols.

Analyze and resolve complex software defects through root cause investigation and corrective action planning.

Research and adopt emerging technologies in embedded systems, AI/ML, and cloud-native automation.

Knowledge and Skills Applied:

Programming Languages: Python, C++, Java.

Embedded Systems: Android Automotive (AAOS), Google Automotive Services (GAS).

Test Automation: Robot Framework, XML configuration, Python scripting.

Cloud & AI/ML Tools: PyTorch, TensorFlow, Google Cloud Platform (GCP), Docker, Kubernetes (K8s), MLOps pipelines.

Infrastructure & Deployment: GPU utilization, distributed training, cloud-native infrastructure, containerization/orchestration.

Simulation & Validation: Calibration techniques, debugging methodologies, reproducibility practices.

Version Control & Issue Tracking: Git, Jira, ALM (Application Lifecycle Management).

Automotive Infotainment Architecture: Multimedia, connectivity, and lifecycle management.

Test Automation Design: Connectivity, navigation, and voice functions.

Advanced AI: Transformer/LLM models for natural language processing and intelligent infotainment features.

Automotive Communication Protocols: CAN, LIN, Ethernet AVB.

Collaboration: OEM/Tier-1 supplier workflows, integration testing, and cross-functional communication.

Defect Management: Root cause analysis, anomaly correction, and corrective action planning.

Innovation & Research: Emerging tools, embedded systems, and AI/ML advancements.

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Master's degree in Electrical Engineering or Computer Science.

3 years of experience in software development, testing, or ML infrastructure.

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Cienet Technologies

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