PhD Intern - Research - Model Alignment 🎓

Are you excited about advancing the next generation of intelligent design systems? Do you want to explore how reinforcement learning can make generative models more adaptive, diverse, and aligned with human creativity? If you're passionate about this, keep reading!

In this role, you will join Autodesk’s Research team, focusing on advancing reinforcement learning for generative design models. You will develop and evaluate new algorithms that help models self-improve, learn from feedback, and generalize across diverse generation tasks. Working closely with senior research scientists, you’ll prototype and test ideas that could lead to real-world impact in Autodesk products such as Fusion and AutoCAD, as well as publishable insights in the broader research community.

This is an exciting opportunity to contribute to Autodesk’s mission of building AI that truly understands and amplifies human design intent, helping shape the future of creative automation.

Responsibilities

• Conduct research on self-play reinforcement learning (RL) methods for structured generative tasks

• Design and implement RL-based alignment frameworks using PyTorch, Ray, and RayLightning for distributed training

• Prototype and test algorithms that improve the validity, diversity, and stability of generated results

• Collaborate with Autodesk Research scientists and engineers to integrate learned models into real-world generative workflows

• Document findings and potentially contribute to a peer-reviewed publication (e.g., NeurIPS, ICLR, ICML)