Cloud Infrastructure Engineer
Rhoda AI - Mountain View, Mountain View,, California, United States
Posted Apr 14, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- 401(k) match
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Schedule
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- Weekend work
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Application
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Where they hire
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About this role
Cloud Infrastructure Engineer Mountain View, Mountain View,, California, United States At Rhoda AI, we're building the next generation of generalist intelligent robots. 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. We've raised over $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for a Cloud Infrastructure Engineer to build and operate the systems that power our robotics and AI platform. You'll own the infrastructure that collects training data, keeps our robots running in the field, and trains and evaluates our models - designing for high reliability and low latency across every layer. The systems you build will be the backbone of what we ship. What You'll Do - Design, build, and maintain cloud infrastructure supporting data collection pipelines, robot operations, and model training and evaluation workflows - Own the reliability, availability, and latency of core infrastructure including databases, data warehouses, and object storage systems - Develop and maintain backend services and APIs that expose infrastructure capabilities to internal teams and customers - Identify and resolve performance bottlenecks across the data and compute stack to meet latency and throughput requirements - Partner with research teams to understand model training and evaluation infrastructure
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