Background
We are a forward-looking AI team within the automotive industry, focused on transforming in-cabin experiences through intelligent Human-Machine Interface (HMI) Cockpit Domain Controller (CDC) systems.
To support our next phase of innovation, we are seeking a SeniSensFusion Engineer with deep expertise in vision/multi-sensfusion, a proven track record in deploying AI models (including multimodal models) on resource-constrained embedded systems.
Key Responsibilities
- Model Development & Deployment: Design cockpit environment/in-cabin perception user interaction stacks fintelligent cockpit scenarios which involve multi-source sensors (vision, in-cabin/out-cabin sensors) multimodal fusion.
- System Integration: Develop integrate necessary software stacks (database, message queue, AI inference framework etc.) real-time embedded environments, ensuring robust communication with vehicle sensors, cloud services, user interface components.
- Production-Quality Code: Write clean, maintainable, highly reliable code in C++ Python. Champion best practices fsoftware development, including code reviews, unit testing, CI/CD.
- Performance Optimization: Profile optimize AI workloads on NVIDIA Qualcomm platforms to meet stringent real-time performance thermal constraints.
- Cross-Functional Collaboration: Work closely with software engineers, system engineers, AI scientists hardware teams to define requirements, troubleshoot complex issues, deliver cohesive, end-to-end features.
Required Qualifications
- Master’s degree in Computer Science, Electrical Engineering related field.
- 5+ years of professional software development experience, with a proven track record of shipping complex software products in ADAS Intelligent Cockpit related areas. (3+ years fexceptional candidates)
- 3+ years of AI algorithm R&D experience, familiar with multimodal model architectures
- Expert-level proficiency in modern C++, with strong experience in multi-threading, memory management, systems programming.
- Proven experience deploying deep learning models on NVIDIA chipset, Qualcomm chipset, similar SoCs.
- Excellent problem-solving skills ability to work in a fast-paced, collaborative environment.
Preferred Qualifications
- Familiarity with Agent-based AI systems.
- Experience with containerization technologies like Docker CI/CD pipelines (e.g., Jenkins, GitLab CI).
- Rich experience in the automotive industry, particularly with AUTOSAR, infotainment systems, Cockpit Domain Controllers.
What We Offer
- Opportunity to shape the future of AI-driven in-cabin experiences.
- Access to cutting-edge hardware tools (AI training hardware latest AI Box hardware).
- Collaborative, innovation-driven culture with a strong focus on AI research-to-product transition.
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