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Machine Learning Engineer – HPC

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Meshy LLC

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Location:
China , Shanghai

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

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.

Job Responsibility:

  • Design, implement, and optimize GPU computing kernels to accelerate model training and inference for next-generation 3D GenAI models
  • Develop and maintain domain-specific libraries and performance-critical components for 3D generation workloads
  • Work closely with researchers and infra engineers to identify bottlenecks, benchmark performance, and deliver high-efficiency, production-ready GPU modules

Requirements:

  • Hands-on experience with CUDA and GPU programming
  • Strong programming skills in C++ and Python
  • Solid understanding of parallel programming, performance tuning, and numerical computation

Nice to have:

  • Experience with quantization, model compression, or other efficiency-oriented model optimization techniques
  • Knowledge of computer graphics, rendering pipelines, or geometry processing
  • Familiarity with GPU profiling tools (e.g., Nsight, nvprof) or hardware-aware optimization

Additional Information:

Job Posted:
February 18, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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