MeshyAI

Systems Engineer

• Help build the world's largest end-to-end 3D native machine learning systems.
• Build the end to end ML framework dedicated for 3D, from pretraining, to finetuning, inferencing, etc.
• Work closely with researchers to co-design the next frontier of 3D & Spatial AI.
• Build and debug on top of modern PyTorch, for maximum parallelism and efficiency.
• Identify bottlenecks and optimize for high throughput & efficient distributed model training.
• Implement and maintain 3D specific custom operators in Triton or CUDA.
• Build efficient inference endpoints with complex multi-stage model pipelines.
• Optimize models through compilation, fusion, quantization, etc.

ML System Engineer, Generative AI

Full-stack Engineer

• Specialize in areas aligned with your strengths and interests — whether Machine Learning, Infrastructure, Data, Frontend, Fullstack, Backend.
• Design, develop, and maintain high-quality software across our tech stack from low-level infrastructure to user-facing products.
• Collaborate with AI researchers, engineers, product managers, designers to deliver features and improvements.
• Write clean, efficient, and well-documented code with a focus on maintainability.
• Participate in code reviews, debugging, and performance optimization.
• Contribute ideas to shape the direction of our products and technical infrastructure.
• Learn and adapt to new tools, technologies, and frameworks as needed.

Software Engineer, New Grad

Infrastructure Engineer

• Architect pipelines across cloud object storage (S3, GCS, Azure Blob), data lakes, and metadata catalogs.
• Optimize large-scale processing with distributed frameworks (Spark, Dask, Ray, Flink, or equivalents).
• Implement partitioning, sharding, caching strategies, and observability (monitoring, logging, alerting) for reliable pipelines.
• Design, implement, and maintain distributed ingestion pipelines for structured and unstructured data (images, 3D/2D assets, binaries).
• Build scalable ETL/ELT workflows to transform, validate, and enrich datasets for AI/ML model training and analytics.
• Support preprocessing of unstructured assets (e.g., images, 3D/2D models, video) for training pipelines, including format conversion, normalization, augmentation, and metadata extraction.
• Implement validation and quality checks to ensure datasets meet ML training requirements.
• Collaborate with ML researchers to quickly adapt pipelines to evolving pretraining and evaluation needs.
• Use infrastructure-as-code (Terraform, Kubernetes, etc.) to manage scalable and reproducible environments.
• Integrate CI/CD best practices for data workflows.
• Maintain data lineage, reproducibility, and governance for datasets used in AI/ML pipelines.
• Work cross-functionally with ML researchers, graphics/vision engineers, and platform teams.
• Embrace versatility: switch between infrastructure-level challenges and asset/data-level problem solving.
• Contribute to a culture of fast iteration, pragmatic trade-offs, and collaborative ownership.

Senior Research Infrastructure Engineer

Data Scientist

• Design and deploy high-impact ML solutions, including recommendation systems, user segmentation, churn prediction, and LTV/revenue forecasting to drive engagement and monetization.
• Apply NLP techniques to analyze unstructured data (e.g., churn feedback) and uncover actionable product and business insights.
• Leverage both structured (schema-ready) and raw datasets to identify high-value modeling opportunities aligned with company priorities.
• Design and evaluate experiments to measure model performance and quantify business impact.
• Translate complex analytical outputs into clear, decision-ready insights and present findings to senior leadership to influence strategic direction.
• Help define Meshy’s long-term data science roadmap and establish best practices in modeling, experimentation, and measurement.
• Mentor junior team members through technical guidance, code reviews, and modeling leadership, strengthening overall team capability.

Senior Data Scientist

Marketing

• Develop and implement B2B marketing strategies to enhance brand awareness and drive market share growth, particularly within the gaming and 3D industries.
• Collaborate closely with the Sales team to align marketing strategies with sales goals, providing the necessary content, collateral, and insights to support lead generation and conversion.
• Create targeted marketing materials that empower the Sales team to engage prospects effectively and move them through the sales funnel.
• Conduct market research to identify customer needs, competitive trends, and new opportunities, helping to inform both marketing and sales strategies.
• Monitor and optimize the effectiveness of marketing efforts in collaboration with the Sales team, adjusting strategies to improve lead quality and sales performance.
• Working in a startup environment is essential, where both strategic thinking and hands-on execution are required to drive success.

Senior B2B Marketer

Product Manager

• Own and drive key enterprise and commercial product areas including API, security, access control, and enterprise analytics, in partnership with our engineering and design teams
• Partner closely with sales, support, and marketing to understand enterprise requirements and support deal cycles
• Collaborate with platform teams to optimize our GTM workflows and platforms
• Identify and prioritize key enterprise workflows and integration points that drive organizational value and expansion

Product Manager – Enterprise, Commercial

Machine Learning Engineer

• Collaborate with Machine Learning engineers to drive progress in AI and graphics R&D
• Build end-to-end ML framework dedicated for 3D
• Debug and monitor hardware platform
• Build training framework and scale data pipelines
• Co-design novel model architectures with researchers

Machine Learning Systems Intern

• Participate in the design and implementation of distributed task orchestration systems using Temporal or Celery.
• Architect pipelines across cloud object storage (S3, GCS), data lakes, and metadata catalogs.
• Implement partitioning, sharding, and caching strategies to ensure data processing pipelines are resilient, highly available, and consistent.
• Design, implement, and maintain distributed ingestion pipelines for structured and unstructured data (images, 3D/2D assets, binaries).
• Build scalable ETL/ELT workflows to transform, validate, and enrich datasets for AI/ML model training and analytics.
• Support preprocessing of unstructured assets (e.g., images, 3D/2D models, video) for training pipelines, including format conversion, normalization, augmentation, and metadata extraction.
• Implement validation and quality checks to ensure datasets meet ML training requirements.
• Collaborate with ML researchers to quickly adapt pipelines to evolving pretraining and evaluation needs.
• Use infrastructure-as-code (Terraform, Kubernetes, etc.) to manage scalable and reproducible environments.
• Manage data assets using Databricks Asset Bundles (DABs) and build rigorous CI/CD pipelines (GitHub Actions).
• Focus on maximizing cluster utilization (CPU/Memory) and optimizing EC2 instance allocation to aggressively reduce compute costs.
• Take ownership of the platform’s "Interface" by building Data Explorers and management consoles using React or Next.js.
• Actively listen to researchers and data scientists to iterate on UI/UX based on their feedback.
• Simplify complex CLI operations into intuitive GUI interactions to boost overall developer experience (DevEx).

Junior Research Infrastructure Engineer

Human Resources

• Partner with executive leadership to build and execute people strategies that support our growth and evolving organizational needs.
• Lead initiatives to strengthen company culture, enhance cross-border collaboration, and foster a high-performing, inclusive work environment.
• Drive the recruitment of top-tier talent in AI, engineering, product, and other critical functions, with a focus on building a strong employer brand in the tech ecosystem.
• Set up and refine HR policies, processes, and systems that are compliant, scalable, and aligned with best practices for high-growth startups.
• Build and implement frameworks for performance reviews, compensation planning, employee development, and retention.

Head of Human Resources

AI Research Scientist

• Design, train, and refine large-scale 3D generative models
• Bridge the gap between cutting-edge research and product
• Create novel model architectures for 3D generation
• Collaborate with infrastructure and systems teams to build scalable training
• Share insights and breakthroughs through internal demos or technical reports

Generative AI Researcher Intern

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

• 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

• 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)

AI Infrastructure Engineer

Account Executive

• Build strong relationships with customers and position Meshy as an indispensable tool in 3D workflows.
• Deliver on revenue targets.
• Develop and maintain a healthy deal pipeline.
• Accurately forecast and report on your business.
• Manage and qualify inbound leads.
• Represent Meshy at industry events and conferences.
• Travel regularly to meet customers and attend events.
• Monitor market trends, competitor activity, and customer feedback to inform sales strategy and product development.