AI Data Infrastructure Engineer

About Us

Ropedia is a Singapore-based, early-stage AI startup focused on building the data infrastructure for spatial and physical intelligence. Our core team brings together expertise from Tsinghua, Meta, Google, and UC Berkeley, and we have already achieved early-stage commercial viability.

We develop proprietary wearable and mobile capture devices and models to collect, recover, and reconstruct multimodal human Xperience in real-world scenarios. Our mission is to power the next generation of World Models and Embodied AI. We offercompensation competitive with top-tier tech giants, along with significant early-team equity and incentives.

Role Overview

Location: Singapore

Type: Full-time

Key Responsibilities

• Build reliable data acquisition and upload pipelines from edge devices to the cloud.
• Design large-scale storage, metadata management, and indexing systems for multimodal 4D datasets.
• Develop dataset versioning, sampling, and filtering tools to support research and engineering teams.
• Provide efficient data loading, caching, and preprocessing capabilities for training pipelines.

Requirements

• Strong engineering experience in backend development, data infrastructure, or distributed systems.
• Proficient in Python, and familiar with at least one backend language (e.g., Go, Rust, or Java).
• Experience with databases, message queues, and object storage systems (e.g., PostgreSQL, Kafka, S3, etc.).
• Familiarity with major cloud service providers.
• Understanding of GPU-based deep learning algorithm deployment.
• Experience with Docker and Kubernetes is a plus.