Research Member of Technical Staff – Data Infrastructure

About the role

Rhoda AI is building generalist intelligent robots and needs a senior engineer to design and scale the data infrastructure that powers its model training pipelines. You will own the end‑to‑end system that ingests, stores, indexes, and serves billions of video clips and multimodal data.

Key responsibilities

• Architect, build, and scale high‑throughput data pipelines handling petabyte‑scale video and sensor data with strong reliability, latency, and cost guarantees.
• Design and optimize large‑scale storage solutions (cloud object storage, databases, metadata stores) for multimodal datasets.
• Develop efficient indexing and retrieval systems for fast dataset querying and iteration.
• Implement observability frameworks, including monitoring, alerting, failure recovery, and performance optimization.
• Manage data artifacts, versioning, and lineage to ensure reproducibility across training runs.
• Build internal tools and interfaces that enable researchers and engineers to explore and analyze large datasets at scale.

Required profile

• 5+ years of experience in data infrastructure, distributed systems, or ML infrastructure.
• Proven track record building and operating large‑scale data pipelines (1B+ samples or petabyte‑scale systems).
• Deep understanding of distributed systems, databases, indexing strategies, and cloud storage architectures.
• Experience optimizing data throughput, workload balancing, and cost‑performance trade‑offs in cloud environments.

Required skills

• Distributed compute frameworks such as Ray or Spark.
• Cloud object storage and database technologies.
• Observability and monitoring tools for high‑scale systems.
• Data versioning and lineage tools (e.g., DVC, Delta Lake).
• Familiarity with data warehouse platforms like Snowflake, BigQuery, or Redshift.