AI Research Engineer Intern

Renesas Electronics•San Jose, CA

1d•$31 - $48•Hybrid

About The Position

The Gen5 Model Development team at Renesas Electronics is advancing next-generation AI systems for automotive applications, focusing on foundation models, causal reasoning, video understanding, and deployment on edge automotive SoCs. We are seeking motivated AI research interns to help develop advanced AI technologies for ADAS and autonomous driving. The selected intern will work on developing a Causal ADAS Foundation Model that can understand complex driving scenes, identify causally relevant agents, predict future risk, and support safer trajectory planning. This internship combines research and engineering across autonomous driving, video foundation models, multi-modal AI, causal reasoning, risk prediction, trajectory planning, and edge AI deployment. Interns will collaborate with researchers and engineers on work that may lead to publications, patents, and deployment on Renesas automotive platforms.

Requirements

Currently pursuing a BS, MS, or PhD in Computer Science, AI, Machine Learning, Robotics, Electrical Engineering, or a related field.
Strong programming skills in Python.
Experience with PyTorch or TensorFlow.
Good understanding of machine learning, deep learning, computer vision, and neural network architectures.
Strong analytical and problem-solving skills.
Experience in one or more areas such as Autonomous Driving, Large Language Models (LLMs), Vision-Language Models (VLMs), Vision-Language-Action (VLA) Models, World Models, Reinforcement Learning, Causal AI, Multi-modal Learning, Robotics, ONNX, TensorRT, or Edge AI deployment.

Responsibilities

Develop and evaluate AI models for video-based driving scene understanding.
Design methods to identify causal factors influencing driving decisions.
Build models for risk prediction, collision forecasting, and safety assessment.
Develop trajectory prediction and planning models for ADAS applications.
Create counterfactual and intervention-based evaluation pipelines.
Benchmark models against state-of-the-art open-source and commercial baselines.
Optimize models for deployment on Renesas automotive hardware platforms.
Document findings and contribute to technical reports, publications, or patent disclosures.