Apply on Employer Site

MeshyAI · 1 day ago

Machine Learning System Engineer

Multnomah County, OR

Full-time

Onsite

Mid Level

MeshyAI is a leading 3D generative AI company headquartered in Silicon Valley, focused on transforming the content creation pipeline for 3D assets. They are seeking Machine Learning Systems Engineers to build end-to-end machine learning systems dedicated to 3D, involving tasks from pretraining to deployment.

Computer Software

Responsibilities

Work within the AI model team to streamline 3D data into high-throughput pipelines and scale training infrastructure to hundreds of GPUs

Train, accelerate, and deploy machine learning models for 3D GenAI

Design and implement reliable and scalable distributed training pipelines, optimize end-to-end training efficiency

Work closely with researchers, software engineers, and artists to integrate AI models into production

Work closely with researchers to build the training infrastructure for our in-house foundational models

Identifying bottlenecks and optimizing for high throughput & efficient distributed model training across hundreds to thousands of GPUs

Building and maintaining training clusters and job schedulers

Implementing and maintaining 3D specific custom operators in Triton or CUDA

Building efficient inference endpoints with complex model pipelines

Optimizing models through compilation, fusion, quantization, etc

Qualification

Machine Learning3D GraphicsDistributed TrainingPyTorchPythonC++Performance OptimizationCommunication Skills

Required

Experience in machine learning or high performance graphics

Solid practical understanding of at least one machine learning framework (e.g. PyTorch, Flax)

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

Preferred

A strong passion to navigate through the PyTorch internals, with hands-on experience in areas like torch.compile, fully_shard (FSDP2) APIs

Experience with building Triton kernels

Experiences with large-scale distributed training, familiarity with modern parallelization techniques: DP, TP, CP, PP, zero redundancy optimizers, etc

Experience with diffusion models in 3D or video

Experience with full bf16 or partially fp8 training