Senior AI Data Infrastructure Engineer
at Meshy · 101-250 employees
Series B · $400M · Jul 2026
- Seniority
- Senior
- Employment
- Full Time
- Location
- Shanghai
- Posted
- 5d ago
kubernetesterraformsnowflakedatabrickssparkci/cd
at Meshy · 101-250 employees
Meshy is a company building foundation models for AI-powered 3D generation that produce production-ready, printable, and game-ready 3D models from text or images.
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 THE ROLE Meshy is building the next generation of 3D generative AI models. Underpinning all of this is our constantly evolving data infrastructure – from the ingestion of massive amounts of raw data to large-scale distributed processing, and the construction of high-quality datasets needed for model training. Data infrastructure is one of our core technological moats and a decisive factor in the research team's ability to iterate rapidly and continuously. We are currently recruiting a Senior Data Infrastructure Engineer in Shanghai to join the Data Infra team and work with engineers worldwide to design, build, and operate distributed data systems that support large-scale AI model training. You will be handling both regular structured data and unstructured assets such as images, 3D models, and videos – the latter typically requiring specialized processing and transformation for pre-training and fine-tuning. This is a versatile role: you will have ownership of an end-to-end data pipeline from data ingestion to transformation and training readiness; you will work closely with ML research teams to prepare various datasets for cutting-edge model training; and you will find your perfect fit in a fast-paced, adaptable, and hands-on startup environment. It's important to note that this is not a data warehousing/BI/data analysis role. The main focus of daily work is on processing pipelines for large-scale unstructured data, optimizing computing and storage efficiency, and ensuring the quality of training data, rather than report and metric modeling. KEY RESPONSIBILITIES - Data Pipeline Construction: Design and maintain highly scalable ETL/ELT pipelines to support the ingestion and processing of structured and massive amounts of unstructured data (images, videos, 3D/2D assets). - Distributed System Optimization: Optimize data processing using frameworks such as Spark/Ray/Flink based on cloud object storage and data lakes, implementing data sharding, caching, and a robust monitoring and alerting mechanism. - AI/ML Data Support: Responsible for the preprocessing (format conversion, enhancement, feature extraction, etc.) and quality verification of model pre-training data, ensuring the lineage and reproducibility of datasets. - Infrastructure and Agile Collaboration: Manage environments using IaC tools such as Terraform/Kubernetes, promoting CI/CD best practices; collaborate closely across teams to quickly respond to R&D needs. JOB REQUIREMENTS - Qualifications and Languages: 5+ years of experience in data engineering or distributed system development; basic English communication skills, capable of conducting all-English meetings and written communication. - Data Pipeline Construction: Design and maintain highly scalable ETL/ELT pipelines to support the ingestion and processing of structured and massive amounts of unstructured data (images, videos, 3D/2D assets). - Distributed System Optimization: Optimize data processing using frameworks such as Spark/Ray/Flink based on cloud object storage and data lakes, implementing data sharding, caching, and a robust monitoring and alerting mechanism. - AI/ML Data Support: Responsible for the preprocessing (format conversion, enhancement, feature extraction, etc.) and quality verification of model pre-training data, ensuring the lineage and reproducibility of datasets. - Infrastructure and Agile Collaboration: Manage environments using IaC tools such as Terraform/Kubernetes, promoting CI/CD best practices; fostering close cross-team collaboration and rapid response to R&D needs. PREFERRED QUALIFICATIONS - Familiarity with the entire training workflow for large models or machine learning (Pre-training/Fine-tuning/RL). - Experience in 3D/2D asset processing (geometric transformation, texture processing) or familiarity with mainstream rendering engines (Blender/Unity/Unreal) for compositing data generation. - Practical experience in Kubernetes distributed workload orchestration or GPU/HPC clusters. - Extensive experience using large-scale data warehouse/lake warehouse platforms (Databricks/Snowflake/BigQuery, etc.). - High-quality open-source contributions in ML Infrastructure and distributed systems, or familiarity with data security and compliance. OUR VALUES - Brain: We value intelligence and the pursuit of knowledge. Our team is composed of some of the brightest minds in