Additional Information
About Meshy
Headquartered in Silicon Valley , Meshy is the leading 3D generative AI company on a mission to Unleash 3D Creativity by transforming the content creation pipeline. Meshy makes it effortless for both professional artists and hobbyists to create unique 3D assets-turning text and images into stunning 3D models in just minutes. What once took weeks and cost $1,000 now takes just 2 minutes and $1.
Our world-class team of top experts in computer graphics, AI, and art includes alumni from MIT, Stanford, and Berkeley, as well as veterans from Nvidia and Microsoft. Our talent spans the globe, with team members distributed across North America, Asia, and Oceania , fostering a diverse and innovative multi-regional culture focused on solving global 3D challenges. Meshy is trusted by top developers, backed by premiere venture capital firms like Sequoia and GGV , and has successfully raised $52 Million in funding.
Meshy is the market leader, recognized as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games) and No.1 in website traffic (according to SimilarWeb, with 3 Million monthly visits). The platform boasts over 5 Million users and has generated 40 Million models .
Founder and CEO Yuanming (Ethan) Hu earned his Ph.D. in graphics and AI from MIT, where he developed the acclaimed Taichi GPU programming language (27K stars on GitHub, used by 300+ institutes). His work is highly influential, including an honorable mention for the SIGGRAPH 2022 Outstanding Doctoral Dissertation Award and over 2,700 research citations.
About this role
We are seeking a Software Engineer Intern to join our Data Infra team and help improve our model evaluation and visualization platform. You will act as the engineering counterpart to a cutting-edge research team, enforcing standards and building infrastructure to empower evaluation of the next generation of 3D models. You will work across backend, infrastructure, frontend, and performance to build foundations for product iteration.
You will be paired with a senior engineer who owns the platform, and you will ship real features end-to-end alongside them. You will thrive in our fast-paced startup environment, where problem-solving, adaptability, and AI-assisted development are the norm.
You'll gain exposure to
AI-assisted software development at production scale - Claude Code, custom skills, agent-driven workflows
Cloud infrastructure on AWS - S3, IAM, multi-region patterns
Production databases (Postgres) and data-migration patterns
Kubernetes and container orchestration
CI/CD pipelines and deployment automation
Web performance engineering and 3D asset delivery
Modern Python web stack - FastAPI, HTMX, Jinja2, Tailwind
What Projects You'll Work On
Design and operate CI/CD pipelines covering lint, type-check, tests, container builds, and deployment to Kubernetes
Build and evolve the data layer - relational schemas, migrations, S3-backed asset storage, and safe cutover strategies
Stand up and operate multi-region web services - replication, CDN, region-aware routing, and per-region observability
Improve API performance and reliability - query optimization, caching, and signed-URL access patterns
Profile and optimize web application performance - page load, Web Vitals, lazy loading, prefetching, and HTTP caching
Optimize delivery of large 3D/2D assets - format selection, compression, and level-of-detail strategies
Build user-facing features in collaboration with researchers and data scientists; iterate on UI/UX based on their feedback
What Makes the Work Interesting
You serve as the engineering counterpart to a cutting-edge research team - your infrastructure directly shapes how the next generation of 3D models gets evaluated
Real-world performance challenges unique to 3D - large asset delivery, WebGL rendering, cross-region latency
Multi-region cloud architecture with measurable cost and latency trade-offs
Direct collaboration with researchers and data scientists - fast feedback loops, no PM funnel
Pair-programming with a senior engineer mentor - learn by shipping real features together, not by watching
A team that uses Claude Code, custom skills, and agent-driven workflows daily - see what AI-native engineering looks like in practice