MeshyAI

Artificial Intelligence

• Build and optimize high-performance graphics components—rendering kernels, geometry processing operators, and supporting systems.
• Develop robust production-quality pipelines that integrate with data pipelines, generative models and artist-facing applications.
• Work across GPU clusters, cloud environments, and local DCC tools to ensure seamless interoperability and scalability.
• Collaborate closely with artists, product teams, and ML researchers to translate creative requirements into technical implementations.
• Contribute to internal tooling, demos, documentation, open-source initiatives, or technical reports that elevate Meshy’s graphics capabilities.

Generative AI – Graphics Engineer

• Design, train, and refine large-scale 3D generative models from covering pre-training, post-training, and emerging paradigms in diffusion, flow matching, and multi-modal learning.
• Bridge the gap between cutting-edge research and product, deploy models in real products used by millions of creators, using human feedback and creative evaluation.
• Create novel model architectures to make 3D generation faster, higher-quality, and more controllable.
• Collaborate with infrastructure and systems teams to build scalable training, and data pipelines across GPU clusters and cloud environments.
• Bring engineering discipline into an fast-paced research environment: elegant code, reproducible experiments, and building software as a team.
• Share insights and breakthroughs through internal demos, open-source contributions, or technical reports that advance the field of 3D generative AI.

Generative AI, 3D Foundation Model

Data Scientist

• Support the development and validation of machine learning models, including recommendation systems, user segmentation, and churn prediction
• Assist in building LTV and revenue forecasting models to support growth and monetization strategy
• Design and analyze experiments to evaluate model effectiveness and business impact
• Conduct exploratory data analysis across both structured (schema-ready) and raw datasets
• Build dashboards and clear data narratives to communicate findings effectively
• Collaborate with Product, Growth, and Engineering teams to translate insights into actionable strategies and measurable business impact

Data Science Intern

Infrastructure Engineer

• Own production reliability: availability, latency, error budgets, incident response, postmortems, and follow-ups
• Build/maintain observability: metrics, logs, traces, alerting, SLOs/SLIs, dashboards
• Improve deployment safety: CI/CD, rollout strategies (canary/blue-green), automated rollback, runbooks
• Capacity planning + cost control: GPU/CPU sizing, autoscaling, queue/backpressure management, cost attribution
• Security + compliance: secrets management, least privilege, patching, vulnerability response
• Disaster recovery + operational readiness: backups, failover plans, game days
• Develop and maintain the GPU inference serving stack (APIs, schedulers, workers, batching, caching)

Generative AI – Graphics Engineer

Generative AI, 3D Foundation Model

Data Science Intern

AI Infrastructure Engineer