Meshy
3D generative AI
GenerativeAI-MLSystemEngineering
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Generative AI - ML System Engineering at Meshy. Skills: Machine Learning Systems Engineering, 3D Generative AI, ML Frameworks, Distributed Training, Inference Optimization. build the world's largest end-to-end 3D native machine learning systems. build our end to end ML framework dedicated for 3D, from pretraining, to finetuning, inferencing, etc.”
What You'll Achieve.
build the world's largest end-to-end 3D native machine learning systems; build our end to end ML framework dedicated for 3D; unleash creativity; generate real value
Industry & Context.
debugging; identifying bottlenecks; performance sense
spend part of their time on-site in our office in Shanghaieijing/Shenzhen, work under deadlines, observe details at close range
What They're Looking For.
Must Have
Experience in machine learning or high performance graphics, Solid practical understanding of at least one machine learning framework (e. g. PyTorch, JAX), 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 interest in the tiniest detail, communication skills for working in a globally distributed team
Nice to Have
A 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 low precision bf16 or fp8 training
What You'll Do.
build the world's largest end-to-end 3D native machine learning systems
build our end to end ML framework dedicated for 3D
debugging and monitoring the hardware platform
building training framework
scaling high-throughput 3D data pipelines for our foundational training
co-designing novel model architectures with researchers
efficient inference engines for diffusion models and more
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
build clean and intuitive 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
Implementing and maintaining 3D specific custom operators in Triton or CUDA
Implementing and maintaining novel data-loading framework and libraries
Building efficient inference endpoints with complex multi-stage model pipelines
Optimizing models through compilation
How You'll Work.
Team & Collaboration
Work closely with researchers; working in a globally distributed team; communication skills for working in a globally distributed team
Communication Scope
communication skills for working in a globally distributed team; communicate information and ideas so others will understand
Full Job Description
WHO YOU ARE We are looking for Machine Learning Systems Engineers who can help us build the world's largest end-to-end 3D native machine learning systems. You will help us build our end to end ML framework dedicated for 3D, from pretraining, to finetuning, inferencing, etc. We expect a combination of strong hands on engineering skills, eagerness to learn new things, and thrives in a fast-paced, high-ownership environment. WHO WE ARE At Meshy, we believe 3D creation should be boundless and accessible. Our mission statement is simple: unleash creativity. We built a full pipeline for 3D content ranging from text / image to 3D, texturing, texture editing, animation rigging, etc. We also built a vibrant community for our creators, where people can share their work, take inspiration from others, and even use it as an asset marketplace for their games and prototypes. We are the market leader in 3D generative AI, recognized as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games survey), and we generate real value and is used by enterprises (including Meta, Square Enix, Deepmind, etc.) and millions of end users. Meshy is used in game and film production, in 3D printing, in industrial product design, in enablement of novel product features such as user-generated content, and even in training and simulation for robotics and physical AI. YOUR NEXT CHALLENGE 3D is the brave new frontier of Gen AI. Our work here involves a lot of unique new challenges in both training and inference. Your next challenge at Meshy would involve the full stack of AI, from debugging and monitoring the hardware platform, building training framework, scaling high-throughput 3D data pipelines for our foundational training, co-designing novel model architectures with researchers, to the novel challenge of efficient inference engines for diffusion models and more. Here are some examples for each side of the challenge: On the training side - Work closely with researchers to co-design th
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