Research Engineer - Design Generation Modeling
Job Overview
As a Research Engineer in Design Generation Modeling, you will work in collaboration with researchers across the globe to produce artifacts and knowledge that will help us push the state of the art of generative design modeling forward. The role will require developing and implementing experimental training pipelines from data to training to inference.
At the moment, this role is focused on:
Foundation models for design understanding and generation
Visual models for design generation and decomposition
Development of design representations for discrete modeling with MLMs
Primary Responsibilities:
Contribute to the development and optimization of ML data pipelines and training workflows.
Improve internal training codebases and procedures.
Collaborate with research scientists and ML engineers to design and implement experiments, ablation studies, etc.
You’re probably a match if you:
Understand and have experience with distributed training at scale using libraries like DeepSpeed, FSDP, Torch, Titan, etc.
Enjoy diving deep into and understanding complex engineering problems.
Are familiar with the literature around GANs, diffusion modeling, transformer architectures, and vision language modeling.
You have disciplined coding practices and are experienced with code reviews and pull requests.
Have experience working in cloud environments, ideally AWS.
Are passionate about both product-focused and basic research.
Nice to Haves:
Specific experience with modeling design data.
Experience with Graph Neural Networks.
Are able to quickly prototype ML demos with appealing user interfaces. E.g. Gradio and other customized interfaces.