Data Engineering Intern, AI & Analytics - Fall 2026

Rivian and Volkswagen Group Technologies•Palo Alto, CA

1d•$45 - $51•Hybrid

About The Position

Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, we’re addressing the challenges of electric vehicles through technology that will set the standards for software-defined vehicles around the world. The road to the future is uncharted. By combining our expertise across connectivity, AI, security and more, we’ll map a new way forward. Working together, we’ll create a future that’s more connected, more intelligent, more sustainable for everyone. We are seeking an AI Engineer Intern to contribute to research and development across speech, vision, language, and multimodal AI systems. You will work closely with researchers and engineers to build, train, evaluate, and deploy advanced models for conversational and in-vehicle applications. This role offers hands-on experience across the full AI development lifecycle, with an emphasis on scalable, robust, and efficient models. About the About the Data Engineering, AI & Analytics Internship: We are looking for talented interns to join various teams within our Data, AI & Analytics department. Program Details: Timeline: Full-time, September 21 – December 18 Location: Palo Alto, CA By submitting a single application to this posting, you will be considered for all of the following internship tracks: AI Engineer Internship Program Details: Timeline: Full-time, September 21 – December 18 Location: Palo Alto, CA or Irvine, CA

Requirements

Currently pursuing an MS or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field.
Strong Python programming skills and experience with PyTorch or TensorFlow.
Solid understanding of machine learning, deep learning, generative modeling, and reinforcement learning fundamentals.

Nice To Haves

Hands-on experience with diffusion models, SFT, reinforcement learning, imitation learning, or preference-based optimization.
Experience working with multimodal or foundation models.
Exposure to distributed training or large-scale inference systems.
Contributions to research projects, publications, or open-source software.
Familiarity with transformer-based architectures, diffusion models, or modern speech/video/language modeling approaches.
Experience using AI-assisted development tools (e.g., Cursor) for coding, experimentation, or rapid prototyping.
Ability to learn quickly and contribute effectively in a collaborative research and engineering environment.

Responsibilities

Contribute to the research and development of generative and discriminative AI models for: Speech and audio systems, including ASR, TTS, speech-to-speech, speaker modeling, diarization, and audio understanding.
Vision and video understanding, using transformer-based architectures for spatial and spatiotemporal modeling, self-supervised learning, and diffusion-based generative models.
Multimodal and foundation models, such as Vision-Language and Speech-Language Models that integrate visual, audio, speech, and text modalities.
Train, supervised fine-tune (SFT), and evaluate deep learning and foundation models on large, domain-specific datasets.
Apply reinforcement and generative policy learning techniques, including imitation learning, preference-based optimization, and alignment methods (e.g., RLHF, RLAIF, DPO).
Curate, preprocess, and manage multimodal datasets, including audio, image, video, text, and preference or trajectory data.
Design and execute experiments to explore new modeling, generative, and alignment approaches.
Collaborate with cross-functional teams and clearly document experimental workflows and results.