Generative AI Pipeline Engineer Intern

Meshy
ShanghaiPosted 31 March 2026

Job Description

Generative AI Pipeline Engineer Intern WHO YOU ARE You are a motivated student or recent graduate who is passionate about building systems — someone who gets excited about automating workflows, writing clean and reliable code, and making complex pipelines actually work. You have a solid foundation in computer graphics and engineering, and you're eager to apply that in the context of cutting-edge generative AI. You might come from a software engineering background with a deep interest in 3D and computer graphics, or from a Technical Art background with strong programming skills. Either way, you thrive when engineering and creativity intersect. You care about real-world creator impact: you're enthusiastic about how generative AI can comprehend, understand, and elevate human creativity — and you want to be part of building that future. YOUR NEXT CHALLENGE As an intern on the Applied Research team at Meshy, you will help build the connective tissue between our generative models, 3D data, and the tools that researchers and artists use every day. Your focus will be on making workflows reliable, automated, and scalable. The essential functions include, but are not limited to: - Build and automate internal pipelines that connect our generative AI models, 3D data, and production tools — turning fragile manual scripts into reliable, repeatable systems. - Develop evaluation infrastructure that allows researchers to consistently assess model quality and get visual feedback in hours rather than days. - Integrate with DCC tools such as Maya, Blender, or Houdini to support automated asset processing, transformation, and quality validation. - Write clean, well-documented, and reproducible code that the broader team can rely on and build upon. - Identify and eliminate technical bottlenecks across the pipeline, keeping workflows scalable as the team and model complexity grow. WHAT WE'RE LOOKING FOR - Currently pursuing or recently completed a degree in Computer Science, Software Engineering, Digital Media, Animation, Game Development, or a related field. - Strong programming skills in Python — this is a must. You are comfortable writing clean, maintainable, production-quality code, not just scripts. - Solid foundation in computer graphics — you understand how 3D content is structured, rendered, and processed at a technical level (e.g., mesh geometry, shaders, rendering pipelines). - Genuine interest in generative AI — you've explored image, video, or 3D generation tools and are curious about how they work under the hood. - Good communication skills and the ability to work collaboratively across research and engineering contexts. Nice to have: - Proficiency in C++ is a strong plus. - Hands-on experience with DCC tools such as Maya, Blender, or Houdini. - Familiarity with concepts like mesh topology, UV mapping, materials, or rigging. - A portfolio or examples of past 3D or technical work (personal projects are welcome). A LITTLE MORE ABOUT MESHY.AI http://meshy.ai Trusted by Meta, Square Enix, DeepMind, and more, Meshy is redefining 3D creation with generative AI. We empower artists, designers, engineers, hobbyists, and makers to bring immersive worlds, characters, and experiences to reality in minutes instead of months. We value intelligence and the pursuit of knowledge. We are a global team of generative-AI pioneers, computer-graphics veterans, and product builders who believe human expression and enjoyment is the ultimate frontier of computing. We care deeply about our work, our users, and each other. Empathy and passion drive us forward. We have a culture of directness and truthfulness — being direct is the most sincere form of trust and care. We trust our instincts and are not afraid to take bold risks. Meshy was born from a few-hour prototype. Innovation requires courage. LOCATION & WORK ENVIRONMENT This role is based on-site in our Shanghai office. We believe great collaboration happens in person, and you'll ... (truncated, view full listing at source)
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