Human-Centered AI ML Research Intern, 3D/CAD

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.
This is a summer 2025 paid 12-week internship opportunity with the Future Product Innovation (FPI) team of the Human-Centered AI department at TRI. Please note that this internship will be a hybrid in-office role based in Los Altos, CA.
This internship opportunity falls within the Human-Centered AI Division (HCAI). We are an integrated team of ML researchers, behavior scientists, and human-computer interaction experts. At the core of our work, we aim to support people to make better decisions by maximising the best of big data, technology, and insights about why we do what we do.
The Team
The Future Product Innovation (FPI) team is an interdisciplinary team of researchers working at the intersection of generative artificial intelligence (AI), design, engineering, and creativity. Our mission is to accelerate design and engineering processes in the automotive industry.
The Internship
We are seeking a highly motivated and dedicated PhD research intern to join our Future Product Innovation team and push the envelope on what is possible with Generative AI technologies in the domain of automotive product design. The ideal candidate will have a strong background in Mechanical Engineering and Machine Learning or related fields, with demonstrated interest in design and generative AI. In this project, the intern will develop physically and semantically constrained 3D shape generation techniques with applications to CAD.
We will match the intern with mentors based on their experience. Over the course of the project, in addition to Future Product Innovation group meetings, the intern will also participate in all Human-Centered AI division meetings and meetings with stakeholders from relevant Toyota business groups. The intern will be exposed to how interdisciplinary industrial research works and learn from our team as well as the other interns in our division. Furthermore, the intern will engage in strategy discussions about how their research connects to business impact at Toyota. In collaboration with your mentor and other researchers in the department, you will:

Responsibilities

• Scope the project to align to the core research efforts
• Be the primary driver of the technical plan (e.g., study design, model development, analysis plan) with regular feedback from mentors
• Execute the project using TRI resources
• Present the project’s approach and findings in research meetings
• Our goal is that you end the summer with work that is publishable in an academic journal or conference

Qualifications

• Currently enrolled in a PhD program in Mechanical Engineering, Machine Learning (or related fields)
• Experience working with CAD/CAE datasets concerning physical properties
• Experience with deep generative models with 3D applications
• Track record of executing research projects, including publications at top conferences
• Desire to work on challenging open-ended research projects
• Demonstrated ability to work autonomously while soliciting feedback
• Excellent communication and teamwork skills

Preferred Qualifications

• Experience with developing research prototypes
• Experience adapting pre-trained models to specific tasks or domains through fine-tuning or similar techniques

Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.
The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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