Rhoda AI
Research Member of Technical Staff- Data Infrastructure
Mountain View · Staff+
Sponsorship not specifiedDetected 66 days ago
Distributed SystemsBigQuerySnowflakeRedshiftCloud PlatformsMachine LearningSparkData EngineeringRoboticsHardware DesignResearchCollaboration
About the role
- We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.
- We hire across levels - from senior to staff.
Responsibilities
- Architect, build, and scale a high-throughput data infrastructure that processes and manages billions of video clips with strong guarantees around reliability, latency, and cost efficiency
- Design and optimize large-scale storage systems (cloud object storage, databases, metadata stores) for multimodal datasets
- Build efficient indexing and retrieval systems to support fast dataset querying, filtering, and iteration for research and production use cases
- Develop observability frameworks for data pipelines including monitoring, alerting, failure recovery, and performance optimization
- Implement intelligent workload balancing and throughput optimization across distributed compute and storage systems
- Manage data artifacts, versioning, and lineage to ensure reproducibility and traceability across training runs
- Build internal interfaces and lightweight tools that enable researchers and engineers to explore, query, and analyze large datasets at scale
- We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots.
- Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design.
Requirements
- 5+ years of experience in data infrastructure, distributed systems, ML infrastructure, or a closely related field
- Experience optimizing data throughput, workload balancing, and cost-performance tradeoffs in cloud environments
- Experience with distributed compute frameworks such as Ray or Spark for large-scale data processing and transformation
- Experience managing large multimodal datasets
- Familiarity with ML training workflows and data lifecycle management
- Experience with robotics data formats or real-world sensor data (video, proprioception, teleoperation logs)
- Experience with data warehouse technologies (e.g., Snowflake, BigQuery, or Redshift) for large-scale data storage, querying, and analytics
- Familiarity with data versioning and lineage tooling (e.g., DVC, Delta Lake, or similar)
Nice to have
- Nice to Have (But Not Required)
Benefits
- Support integration and scalable deployment of vision-language models (VLMs) within data pipelines for screening, enrichment, or metadata generation
Company info
- What We're Looking For
- At Rhoda AI, we're building the next generation of generalist intelligent robots.
- We're looking for Data Infrastructure MLEs to scale the systems that power our model training data pipeline, from raw ingestion and storage to indexing, retrieval, and throughput optimization at massive scale.
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