Shape the future of 3D AI generation by contributing to foundational research in generative models. As a Generative AI Researcher Intern, you'll work at the intersection of deep learning and 3D graphics, developing novel approaches to model architecture, training efficiency, and high-fidelity texture synthesis.
What You'll Do
- Develop and refine 3D generative models using autoregressive and discrete diffusion frameworks, pushing the boundaries of current capabilities
- Process and analyze 3D meshes, designing tokenization strategies that enable effective model ingestion
- Optimize training pipelines by improving model architecture and memory utilization across CPU and GPU
- Advance texture generation using diffusion and auto-regressive methods to produce sharp, geometrically consistent outputs
- Generate full PBR material stacks that respond realistically to lighting, aligning AI outputs with production-grade standards
Who You Are
- Currently pursuing an undergraduate, master’s, or PhD program with plans to transition into a full-time role after graduation (targeting 2026–2027 or later)
- Committed to a full-time, 12-week (or longer) internship
- Proficient in Python and experienced with tensor programming and transformer-based architectures
- Intrinsically motivated to explore and scale AI systems, grounded in the principles of scaling laws
- Able to break down abstract research goals into actionable technical plans
- Clear communicator who thrives in collaborative, knowledge-sharing environments
- Driven by curiosity and unafraid to tackle emerging challenges in AI and 3D modeling
Our Environment
We operate in a fast-moving, self-directed setting where innovation and execution efficiency are prioritized. The team values deep technical rigor, creative problem-solving, and contributions that advance the state of the art in AI for 3D worlds. If you're passionate about transforming how digital environments are created, this role offers direct impact.
