PhD Intern - Efficient 3D Generation Frameworks Job Toronto area,Ontario Canada,IT/Tech

Position Overview

Are you excited about advancing the future of intelligent 3D content creation? Do you want to explore how learning from feedback can make generative models more efficient, adaptable, and aligned with human intentions? If so, this role is for you.

You will join Autodesk Research to develop efficient 3D generative modeling frameworks that enable rapid sampling and iterative improvement. You will prototype new training approaches that integrate various forms of feedback or guidance, helping models refine and improve their generated output. Working closely with senior research scientists, you’ll develop solutions that can influence real-world products such as Fusion and AutoCAD, while contributing publishable insights to the scientific community.
This is an opportunity to help shape the next generation of AI-driven design tools that truly enhance human creativity.

Responsibilities

Conduct research on accelerated generative modeling for 3D shape synthesis

Develop feedback-driven learning and refinement algorithms

Build efficient training pipelines using Python, PyTorch, and distributed frameworks such as Ray or Ray Lightning

Prototype and evaluate techniques that improve sampling speed, controllability, and diversity in 3D generation

Collaborate with Autodesk Research scientists and engineers to integrate methods into real-world design workflows

Document findings and contribute work suitable for submission to top ML venues (e.g., NeurIPS, ICLR, ICML)

Minimum Qualifications

Currently pursuing a PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline

Strong foundation in generative modeling, deep learning, and (optionally) reinforcement learning or feedback-driven optimization

Proficiency in Python and Py Torch

Understanding of distributed training or experience with Ray/Ray Lightning

Strong analytical and communication skills, with the ability to iterate quickly based on experimental results

Preferred Qualifications

Research experience in efficient generative modeling, 3D representation learning, or feedback-based training

Familiarity with geometric ML, 3D shape representations, or CAD data

Evidence of research impact (publications or preprints in venues such as NeurIPS, ICLR, ICML, CVPR, etc.)

Interest in bridging foundational ML research with real-world generative design applications

Ability to work independently while collaborating across multidisciplinary teams

About the Canada Intern Program

The 2026 Canada Internship program runs for 16 weeks (May 4th – August 21st). All internships are paid. As an intern, you will contribute to meaningful projects, be mentored by industry leaders, and participate in tech talks and other activities designed to support your personal and professional development. Our internships align with Autodesk’s Flexible Workplace approach, which is designed to meet the needs of our business while providing flexibility in support of office, remote and hybrid work preferences.

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience, educational level, and geographic location.

Diversity & Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here:


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