Data Infrastructure Engineer

• Core Data 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.
• Distributed Systems & Storage
  • 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.
• Pretrain Data Processing
  • 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.
• Infrastructure & DevOps
  • Use infrastructure-as-code (Terraform, Kubernetes, etc.) to manage scalable and reproducible environments.
  • Integrate CI/CD best practices for data workflows.
• Data Governance & Collaboration
  • 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.

• Technical Background
  • 5+ years of experience in data engineering, distributed systems, or similar.
  • Strong programming skills in Python (plus Scala/Java/C++ a plus).
  • Solid skills in SQL for analytics, transformations, and warehouse/lakehouse integration.
  • Proficiency with distributed frameworks (Spark, Dask, Ray, Flink).
  • Familiarity with cloud platforms (AWS/GCP/Azure) and storage systems (S3, Parquet, Delta Lake, etc.).
  • Experience with workflow orchestration tools (Airflow, Prefect, Dagster).
• Domain Skills (Preferred)
  • Experience handling large-scale unstructured datasets (images, video, binaries, or 3D/2D assets).
  • Familiarity with AI/ML training data pipelines, including dataset versioning, augmentation, and sharding.
  • Exposure to computer graphics or 3D/2D data processing is strongly preferred.
• Mindset
  • Comfortable in a startup environment: versatile, self-directed, pragmatic, and adaptive.
  • Strong problem solver who enjoys tackling ambiguous challenges.
  • Commitment to building robust, maintainable, and observable systems.

• Kubernetes for distributed workloads and orchestration.
• Data warehouses or lakehouse platforms (Snowflake, BigQuery, Databricks, Redshift).
• Familiarty GPU-accelerated computing and HPC clusters
• Experience with 3D/2D asset processing (geometry transformations, rendering pipelines, texture handling).
• Rendering engines (Blender, Unity, Unreal) for synthetic data generation.
• Open-source contributions in ML infrastructure, distributed systems, or data platforms.
• Familiarity with secure data handling and compliance

Our Values

• Brain: We value intelligence and the pursuit of knowledge. Our team is composed of some of the brightest minds in the industry.
• Heart: We care deeply about our work, our users, and each other. Empathy and passion drive us forward.
• Gut: We trust our instincts and are not afraid to take bold risks. Innovation requires courage.
• Taste: We have a keen eye for quality and aesthetics. Our products are not just functional but also beautiful.

Why Join Meshy?

• Competitive salary, equity, and benefits package.
• Opportunity to work with a talented and passionate team at the forefront of AI and 3D technology.
• Flexible work environment, with options for remote and on-site work.
• Opportunities for fast professional growth and development.
• An inclusive culture that values creativity, innovation, and collaboration.
• Unlimited, flexible time off.