ML System Engineer, Generative AI

Role Overview

• Help build the world's largest end-to-end 3D native machine learning systems.
• Build the end to end ML framework dedicated for 3D, from pretraining, to finetuning, inferencing, etc.
• Work closely with researchers to co-design the next frontier of 3D & Spatial AI.
• Build and debug on top of modern PyTorch, for maximum parallelism and efficiency.
• Identify bottlenecks and optimize for high throughput & efficient distributed model training.
• Implement and maintain 3D specific custom operators in Triton or CUDA.
• Build efficient inference endpoints with complex multi-stage model pipelines.
• Optimize models through compilation, fusion, quantization, etc.

Requirements

• Experience in machine learning or high performance graphics.
• Solid practical understanding of at least one machine learning framework (e.g. PyTorch, JAX).
• Strong ability to write beautiful and maintainable code in Python and/or C++.
• Ability to learn fast and dive into new concepts or complex codebases.
• Performance and efficiency oriented mindset, with a strong interest in the tiniest detail.
• Strong communication skills for working in a globally distributed team.
• A strong passion to navigate through the PyTorch internals, with hands-on experience in areas like torch.compile , fully_shard (FSDP2) APIs (nice to have).
• Experience with building Triton kernels (nice to have).
• Experiences with large-scale distributed training, familiarity with modern parallelization techniques: DP, TP, CP, PP, zero redundancy optimizers, etc. (nice to have).
• Experience with diffusion models in 3D or video (nice to have).
• Experience with low precision bf16 or fp8 training (nice to have).

Tech Stack

• Python
• PyTorch

Benefits

• We value intelligence and the pursuit of knowledge.
• We care deeply about our work, our users, and each other.
• We trust our instincts and are not afraid to take bold risks.
• We have a keen eye for quality and aesthetics.