Job Description

Join to apply for the Staff AI Application Engineer, Edge AI role at Rivian and Volkswagen Group Technologies

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Join to apply for the Staff AI Application Engineer, Edge AI role at Rivian and Volkswagen Group Technologies

About Us

Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotives next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, were addressing the challenges of electric vehicles through technology that will set the standards for software-defined vehicles around the world.

Role Summary

Rivian and Volkswagen Group Technologies, Inc. is seeking a passionate and experienced AI Applications Engineer to join our innovative team. You will be responsible for the design, development, and deployment of cutting-edge AI-driven applications for our software-defined vehicle infotainment platform, leveraging Edge AI capabilities. This role will focus on creating intuitive and intelligent user experiences through applications such as conversational AI assistants and multimodal (vision, video, audio) AI features. You will collaborate closely with cross-functional teams to deliver high-quality, scalable solutions that redefine the in-car experience.

Responsibilities

1. Design, develop, and deploy advanced AI-powered applications for our infotainment system, focusing on areas like conversational AI, computer vision, video analytics, and audio processing.
2. Deliver high-quality, well-tested code, effectively debug complex issues, and manage priorities to meet deadlines with efficiency and a sense of urgency.
3. Collaborate closely with cross-functional teams, including software engineers, AI/ML researchers, UX/UI designers, and product managers, to define requirements, design solutions, and make necessary architectural and design trade-offs for scalable end-to-end AI applications.
4. Research, evaluate, and implement new AI/ML technologies, frameworks, and techniques to enhance application performance, accuracy, and user experience on Edge AI platforms.
5. Stay at the forefront of AI advancements, continuously exploring innovative technologies and approaches, and effectively navigate the complexities of problem-solving in a rapidly evolving field.
6. Contribute to the development and optimization of Edge AI models for efficient deployment and execution within the vehicle environment.
7. Participate in the full software development lifecycle, including requirements gathering, design, implementation, testing, deployment, and maintenance.
8. Leverage your experience with Android development to integrate AI functionalities seamlessly within the infotainment system.

Qualifications

1. Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field with a strong emphasis on AI/Machine Learning.
2. 7+ years of hands-on software development experience, with a strong focus on building applications leveraging AI/ML technologies.
3. Proven experience in developing and deploying applications that utilize one or more of the following: conversational AI, computer vision, video analytics, audio processing, or other multimodal AI techniques.
4. Experience with relevant AI/ML frameworks and libraries such as TensorFlow, PyTorch, ONNX, or similar.
5. Familiarity with cloud-based AI/ML platforms and services (e.g., AWS AI, Google Cloud AI Platform, Azure AI).
6. Some experience building Android applications using Java or Kotlin.
7. Experience with mobile or embedded systems development is highly desirable, particularly in the context of deploying AI models on resource-constrained devices (Edge AI).
8. Strong understanding of data structures, algorithms, and software design patterns relevant to AI application development.
9. Experience in designing and implementing robust APIs for AI-powered features and services.
10. Solid understanding of operating system concepts, including concurrency, inter-process communication (IPC), and performance optimization.
11. Experience with solution design involving data pipelines, feature engineering, and model integration within application workflows.
12. Familiarity with software development best practices, including version control (Git), code review processes (e.g., Gerrit), and build and deployment tools (e.g., Gradle, CMake).
13. Excellent problem-solving, analytical, and communication skills.

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