AI Research Engineer Intern at Renesas Electronics — San Jose, CA

Internship - 3-6 months (start date asap) and extendable

San Jose, CA - Hybrid

About Renesas

Renesas Electronics is a global leader in embedded semiconductor solutions, enabling connected and intelligent devices across automotive, industrial, and IoT markets. The Gen5 Model Development team is advancing next-generation AI systems for automotive applications, with a focus 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.

Internship Overview

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.

Key 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.

Minimum Qualifications

• 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.

What You Will Gain

• Hands-on experience building advanced AI systems for automotive applications.
• Exposure to large-scale autonomous driving datasets and evaluation platforms.
• Opportunity to contribute to research publications, patents, and technical documentation.
• Experience deploying AI workloads on real automotive hardware.
• Mentorship from experts in AI, embedded systems, and autonomous driving.

Deliverables

By the end of the internship, successful candidates are expected to:

• Develop a working prototype of a causal ADAS model or subsystem.
• Benchmark performance against existing baselines.
• Deliver reproducible training and evaluation pipelines.
• Present technical results to engineering leadership.
• Contribute to publication-quality research artifacts or documentation.

The expected hourly pay range for this position is $31.25/hr - $47.75/hr. This position is also eligible for bonus opportunities. Please note that the final offer amount, including any applicable bonuses, will be dependent on geographic location, relevant experience, and skillset of the candidate.

Interns may be eligible for certain Company-provided benefits, which can include sick leave, holiday pay, and medical, dental, and vision insurance. Eligibility and specific benefits will be provided in accordance with Company policy and applicable law.